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【AI 顶会】NIPS2019接收论文完整列表_gate decorator: global filter pruning method for a

作者：IT小白 | 2024-02-29 00:22:00

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gate decorator: global filter pruning method for accelerating deep convoluti

NeurIPS2019

在这里插入图片描述
NeurIPS 2019的论文结果已经出炉，包括了36篇oral和164篇spotlights共1428篇论文。可以看到论文的主题还是以深度学习、神经网络、图、优化、通用性、鲁棒性以及效率等方面为主。详细的列表见下文，官方发布论文链接后会及时同步，如果想及时学习文章可以在主流搜索引擎里搜索论文标题阐释查找预印版论文，作者及实验室主页也是寻找论文的好地方~~~

Tips:哪篇是您感兴趣的论文？可以再留言里和大家分享交流O(∩_∩)O，也可以附上论文链接一起补充列表~~~
1,2, 3

Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation
Risto Vuorio (University of Michigan) · Shao-Hua Sun (University of Southern California) · Hexiang Hu (University of Southern California) · Joseph Lim (University of Southern California

ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks
Jiasen Lu (Georgia Tech) · Dhruv Batra (Georgia Tech / Facebook AI Research (FAIR)) · Devi Parikh (Georgia Tech / Facebook AI Research (FAIR)) · Stefan Lee (Georgia Institute of Technology)

Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers
Liwei Wu (University of California, Davis) · Shuqing Li (University of California, Davis) · Cho-Jui Hsieh (UCLA) · James Sharpnack (UC Davis)

Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video
Jiawang Bian (The University of Adelaide) · Zhichao Li (Tusimple) · Naiyan Wang (Hong Kong University of Science and Technology) · Huangying Zhan (The University of Adelaide) · Chunhua Shen (University of Adelaide) · Ming-Ming Cheng (Nankai University) · Ian Reid (University of Adelaide)

Zero-shot Learning via Simultaneous Generating and Learning
Hyeonwoo Yu (Seoul National University) · Beomhee Lee (Seoul National University)

Ask not what AI can do for you, but what AI should do: Towards a framework of task delegability
Brian Lubars (University of Colorado Boulder) · Chenhao Tan (University of Colorado Boulder)

Stand-Alone Self-Attention in Vision Models
Niki Parmar (Google) · Prajit Ramachandran (Google Brain) · Ashish Vaswani (Google Brain) · Irwan Bello (Google) · Anselm Levskaya (Google) · Jon Shlens (Google Research)

High Fidelity Video Prediction with Large Neural Nets
Ruben Villegas (Adobe Research / U. Michigan) · Arkanath Pathak (Google) · Harini Kannan (Google Brain) · Honglak Lee (Google / U. Michigan) · Dumitru Erhan (Google Brain) · Quoc V Le (Google)

Unsupervised learning of object structure and dynamics from videos
Matthias Minderer (Google Research) · Chen Sun (Google Research) · Ruben Villegas (Adobe Research / U. Michigan) · Forrester Cole (Google Research) · Kevin Murphy (Google) · Honglak Lee (Google Brain)

TensorPipe: Easy Scaling with Micro-Batch Pipeline Parallelism
Yanping Huang (Google Brain) · Youlong Cheng (Google) · Ankur Bapna (Google) · Orhan Firat (Google) · Dehao Chen (Google) · Mia Chen (Google Brain) · HyoukJoong Lee (Google) · Jiquan Ngiam (Google Brain) · Quoc V Le (Google) · Yonghui Wu (Google) · zhifeng Chen (Google Brain)

Meta-Learning with Implicit Gradients
Aravind Rajeswaran (University of Washington) · Chelsea Finn (Stanford University) · Sham Kakade (University of Washington) · Sergey Levine (UC Berkeley)

Adversarial Examples Are Not Bugs, They Are Features
Andrew Ilyas (MIT) · Shibani Santurkar (MIT) · Dimitris Tsipras (MIT) · Logan Engstrom (MIT) · Brandon Tran (Massachusetts Institute of Technology) · Aleksander Madry (MIT)

Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks
Vineet Kosaraju (Stanford University) · Amir Sadeghian (Stanford University) · Roberto Martín-Martín (Stanford University) · Ian Reid (University of Adelaide) · Hamid Rezatofighi (Stanford University // University of Adelaide) · Silvio Savarese (Stanford University)

FreeAnchor: Learning to Match Anchors for Visual Object Detection
Xiaosong Zhang (University of Chinese Academy of Sciences) · Fang Wan (University of Chinese Academy of Sciences) · Chang Liu (University of Chinese Academy of Sciences) · Rongrong Ji (Xiamen University, China) · Qixiang Ye (University of Chinese Academy of Sciences, China)

Differentially Private Hypothesis Selection
Mark Bun (Boston University) · Gautam Kamath (University of Waterloo) · Thomas Steinke (IBM, Almaden) · Steven Wu (University of Minnesota)

New Differentially Private Algorithms for Learning Mixtures of Well-Separated Gaussians
Gautam Kamath (University of Waterloo) · Or Sheffet (University of Alberta) · Vikrant Singhal (Northeastern University) · Jonathan Ullman (Northeastern University)

Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation
Mark Bun (Boston University) · Thomas Steinke (IBM, Almaden)

Multi-Resolution Weak Supervision for Sequential Data
Paroma Varma (Stanford University) · Frederic Sala (Stanford) · Shiori Sagawa (Stanford University) · Jason Fries (Stanford University) · Daniel Fu (Stanford University) · Saelig Khattar (Stanford University) · Ashwini Ramamoorthy (Stanford University) · Ke Xiao (Stanford University) · Kayvon Fatahalian (Stanford) · James Priest (Stanford University) · Christopher Ré (Stanford)

DeepUSPS: Deep Robust Unsupervised Saliency Prediction via Self-supervision
Tam Nguyen (Freiburg Computer Vision Lab) · Maximilian Dax (Bosch GmbH) · Chaithanya Kumar Mummadi (Robert Bosch GmbH) · Nhung Ngo (Bosch Center for Artificial Intelligence) · Thi Hoai Phuong Nguyen (Karlsruhe Institute of Technology (KIT), Germany) · Zhongyu Lou (Robert Bosch Gmbh) · Thomas Brox (University of Freiburg)

The Point Where Reality Meets Fantasy: Mixed Adversarial Generators for Image Splice Detection
Vladimir V. Kniaz (IEEE) · Vladimir Knyaz (State Research Institute of Aviation Systems) · Fabio Remondino ("Fondazione Bruno Kessler, Italy")

You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle
Dinghuai Zhang (Peking University) · Tianyuan Zhang (Peking University) · Yiping Lu (Peking University) · Zhanxing Zhu (Peking University) · Bin Dong (Peking University)

Imitation Learning from Observations by Minimizing Inverse Dynamics Disagreement
Chao Yang (Tsinghua University) · Xiaojian Ma (University of California, Los Angeles) · Wenbing Huang (Tsinghua University) · Fuchun Sun (Tsinghua) · Huaping Liu (Tsinghua University) · Junzhou Huang (University of Texas at Arlington / Tencent AI Lab) · Chuang Gan (MIT-IBM Watson AI Lab)

Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance
Kimia Nadjahi (Télécom ParisTech) · Alain Durmus (ENS Paris Saclay) · Umut Simsekli (Institut Polytechnique de Paris/ University of Oxford) · Roland Badeau (Télécom ParisTech)

Generalized Sliced Wasserstein Distances
Soheil Kolouri (HRL Laboratories LLC) · Kimia Nadjahi (Télécom ParisTech) · Umut Simsekli (Institut Polytechnique de Paris/ University of Oxford) · Roland Badeau (Télécom ParisTech) · Gustavo Rohde (University of Virginia)

First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise
Thanh Huy Nguyen (Telecom ParisTech) · Umut Simsekli (Institut Polytechnique de Paris/ University of Oxford) · Mert Gurbuzbalaban (Rutgers) · Gaël RICHARD (Télécom ParisTech)

Blind Super-Resolution Kernel Estimation using an Internal-GAN
Sefi Bell-Kligler (Weizmann Istitute of Science) · Assaf Shocher (Weizmann Institute of Science) · Michal Irani (Weizmann Institute of Science)

Noise-tolerant fair classification
Alex Lamy (Columbia University) · Ziyuan Zhong (Columbia University) · Aditya Menon (Google) · Nakul Verma (Columbia University)

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection
Bingzhe Wu (Peeking University) · Shiwan Zhao (IBM Research - China) · Haoyang Xu (Peking University) · Chaochao Chen (Ant Financial) · Li Wang (Ant Financial) · Xiaolu Zhang (Ant Financial Services Group) · Guangyu Sun (Peking University) · Jun Zhou (Ant Financial)

Joint-task Self-supervised Learning for Temporal Correspondence
Xueting Li (University of California, Merced) · Sifei Liu (NVIDIA) · Shalini De Mello (NVIDIA) · Xiaolong Wang (CMU) · Jan Kautz (NVIDIA) · Ming-Hsuan Yang (Google / UC Merced)

Provable Gradient Variance Guarantees for Black-Box Variational Inference
Justin Domke (University of Massachusetts, Amherst)

Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation
Justin Domke (University of Massachusetts, Amherst) · Daniel Sheldon (University of Massachusetts Amherst)

Experience Replay for Continual Learning
David Rolnick (UPenn) · Arun Ahuja (DeepMind) · Jonathan Schwarz (DeepMind) · Timothy Lillicrap (DeepMind & UCL) · Gregory Wayne (Google DeepMind)

Deep ReLU Networks Have Surprisingly Few Activation Patterns
Boris Hanin (Texas A&M) · David Rolnick (UPenn)

Chasing Ghosts: Instruction Following as Bayesian State Tracking
Peter Anderson (Georgia Tech) · Ayush Shrivastava (Georgia Institute of Technology) · Devi Parikh (Georgia Tech / Facebook AI Research (FAIR)) · Dhruv Batra (Georgia Tech / Facebook AI Research (FAIR)) · Stefan Lee (Georgia Institute of Technology)

Block Coordinate Regularization by Denoising
Yu Sun (Washington University in St. Louis) · Jiaming Liu (Washington University in St. Louis) · Ulugbek Kamilov (Washington University in St. Louis)

Reducing Noise in GAN Training with Variance Reduced Extragradient
Tatjana Chavdarova (Mila & Idiap & EPFL) · Gauthier Gidel (Mila) · François Fleuret (Idiap Research Institute) · Simon Lacoste-Julien (Mila, Université de Montréal)

Learning Erdos-Renyi Random Graphs via Edge Detecting Queries
Zihan Li (National University of Singapore) · Matthias Fresacher (University of Adelaide) · Jonathan Scarlett (National University of Singapore)

A Primal-Dual link between GANs and Autoencoders
Hisham Husain (The Australian National University) · Richard Nock (Data61, the Australian National University and the University of Sydney) · Robert Williamson (Australian National University & Data61)

muSSP: Efficient Min-cost Flow Algorithm for Multi-object Tracking
Congchao Wang (Virginia Tech) · Yizhi Wang (Virginia Tech) · Yinxue Wang (Virginia Tech) · Chiung-Ting Wu (Virginia Tech) · Guoqiang Yu (Virginia Tech)

Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation
Qiming ZHANG (University of Sydney) · Jing Zhang (The University of Sydney) · Wei Liu (Tencent AI Lab) · Dacheng Tao (University of Sydney)

Invert to Learn to Invert
Patrick Putzky (University of Amsterdam) · Max Welling (University of Amsterdam / Qualcomm AI Research)

Equitable Stable Matchings in Quadratic Time
Nikolaos Tziavelis (Northeastern University) · Ioannis Giannakopoulos (National Technical University of Athens) · Katerina Doka (NTUA) · Nectarios Koziris (NTUA) · Panagiotis Karras (Aarhus University)

Zero-Shot Semantic Segmentation
Maxime Bucher (Valeo.ai) · Tuan-Hung VU (Valeo.ai) · Matthieu Cord (Sorbonne University) · Patrick Pérez (Valeo.ai)

Metric Learning for Adversarial Robustness
Chengzhi Mao (Columbia University) · Ziyuan Zhong (Columbia University) · Junfeng Yang (Columbia University) · Carl Vondrick (Columbia University) · Baishakhi Ray (Columbia University)

DISN: Deep Implicit Surface Network for High-quality Single-view 3D Reconstruction
Qiangeng Xu (USC) · Weiyue Wang (USC) · Duygu Ceylan (Adobe Research) · Radomir Mech (Adobe Systems Incorporated) · Ulrich Neumann (USC)

Batched Multi-armed Bandits Problem
Zijun Gao (Stanford University) · Yanjun Han (Stanford University) · Zhimei Ren (Stanford University) · Zhengqing Zhou (Stanford University)

vGraph: A Generative Model for Joint Community Detection and Node Representation Learning
Fan-Yun Sun (National Taiwan University) · Meng Qu (Mila) · Jordan Hoffmann (Harvard University/Mila) · Chin-Wei Huang (MILA) · Jian Tang (HEC Montreal & MILA)

Differentially Private Bayesian Linear Regression
Garrett Bernstein (University of Massachusetts Amherst) · Daniel Sheldon (University of Massachusetts Amherst)

Semantic Conditioned Dynamic Modulation for Temporal Sentence Grounding in Videos
Yitian Yuan (Tsinghua University) · Lin Ma (Tencent AI Lab) · Jingwen Wang (Tencent AI Lab) · Wei Liu (Tencent AI Lab) · Wenwu Zhu (Tsinghua University)

AGEM: Solving Linear Inverse Problems via Deep Priors and Sampling
Bichuan Guo (Tsinghua University) · Yuxing Han (South China Agriculture University) · Jiangtao Wen (Tsinghua University)

CPM-Nets: Cross Partial Multi-View Networks
Changqing Zhang (Tianjin University) · Zongbo Han (Tianjin University) · yajie cui (tianjin university) · Huazhu Fu (Inception Institute of Artificial Intelligence) · Joey Tianyi Zhou (IHPC, A*STAR) · Qinghua Hu (Tianjin University)

Learning to Predict Layout-to-image Conditional Convolutions for Semantic Image Synthesis
Xihui Liu (The Chinese University of Hong Kong) · Guojun Yin (University of Science and Technology of China) · Jing Shao (Sensetime) · Xiaogang Wang (The Chinese University of Hong Kong) · hongsheng Li (cuhk)

Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling
Andrey Kolobov (Microsoft Research) · Yuval Peres (N/A) · Cheng Lu (Microsoft) · Eric J Horvitz (Microsoft Research)

SySCD: A System-Aware Parallel Coordinate Descent Algorithm
Celestine Mendler-Dünner (UC Berkeley) · Nikolas Ioannou (IBM Research) · Thomas Parnell (IBM Research)

Importance Weighted Hierarchical Variational Inference
Artem Sobolev (Samsung) · Dmitry Vetrov (Higher School of Economics, Samsung AI Center, Moscow)

RSN: Randomized Subspace Newton
Robert Gower (Institut Polytechnique de Paris, Telecom Paris) · Dmitry Koralev (KAUST) · Felix Lieder (Heinrich-Heine-Universität Düsseldorf) · Peter Richtarik (KAUST)

Trust Region-Guided Proximal Policy Optimization
Yuhui Wang (Nanjing University of Aeronautics and Astronautics) · Hao He (Nanjing University of Aeronautics and Astronautics) · Xiaoyang Tan (Nanjing University of Aeronautics and Astronautics, China) · Yaozhong Gan (Nanjing University of Aeronautics and Astronautics, China)

Adversarial Self-Defense for Cycle-Consistent GANs
Dina Bashkirova (Boston University) · Ben Usman (Boston University) · Kate Saenko (Boston University)

Towards closing the gap between the theory and practice of SVRG
Othmane Sebbouh (Télécom ParisTech) · Nidham Gazagnadou (Télécom Paris) · Samy Jelassi (Princeton University) · Francis Bach (INRIA - Ecole Normale Superieure) · Robert Gower (Institut Polytechnique de Paris, Telecom Paris)

Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control
Armin Lederer (Technical University of Munich) · Jonas Umlauft (Technical University of Munich) · Sandra Hirche (Technische Universitaet Muenchen)

ETNet: Error Transition Network for Arbitrary Style Transfer
Chunjin Song (Shenzhen University) · Zhijie Wu (Shenzhen University) · Yang Zhou (Shenzhen University) · Minglun Gong (Memorial Univ) · Hui Huang (Shenzhen University)

No Pressure! Addressing the Problem of Local Minima in Manifold Learning Algorithms
Max Vladymyrov (Google Research)

Deep Equilibrium Models
Shaojie Bai (Carnegie Mellon University) · J. Zico Kolter (Carnegie Mellon University / Bosch Center for AI) · Vladlen Koltun (Intel Labs)

Saccader: Accurate, Interpretable Image Classification with Hard Attention
Gamaleldin Elsayed (Google Research, Brain Team) · Simon Kornblith (Google Brain) · Quoc V Le (Google)

Multiway clustering via tensor block models
Miaoyan Wang (University of Wisconsin - Madison) · Yuchen Zeng (University of Wisconsin - Madison)

Regret Minimization for Reinforcement Learning on Multi-Objective Online Markov Decision Processes
Wang Chi Cheung (Department of Industrial Systems Engineering and Management, National University of Singapore)

NAT: Neural Architecture Transformer for Accurate and Compact Architectures
Yong Guo (South China University of Technology) · Yin Zheng (Tencent AI Lab) · Mingkui Tan (South China University of Technology) · Qi Chen (South China University of Technology) · Jian Chen ("South China University of Technology, China") · Peilin Zhao (Tencent AI Lab) · Junzhou Huang (University of Texas at Arlington / Tencent AI Lab)

Selecting Optimal Decisions via Distributionally Robust Nearest-Neighbor Regression
Ruidi Chen (Boston University) · Ioannis Paschalidis (Boston University)

Network Pruning via Transformable Architecture Search
Xuanyi Dong (University of Technology Sydney) · Yi Yang (UTS)

Differentiable Cloth Simulation for Inverse Problems
Junbang Liang (University of Maryland, College Park) · Ming C Lin (UMD-CP & UNC-CH) · Vladlen Koltun (Intel Labs)

Poisson-randomized Gamma Dynamical Systems
Aaron Schein (UMass Amherst) · Scott Linderman (Columbia University) · Mingyuan Zhou (University of Texas at Austin) · David Blei (Columbia University) · Hanna Wallach (MSR NYC)

Volumetric Correspondence Networks for Optical Flow
Gengshan Yang (Carnegie Mellon University) · Deva Ramanan (Carnegie Mellon University)

Learning Conditional Deformable Templates with Convolutional Networks
Adrian Dalca (MIT, HMS) · Marianne Rakic (MIT/ETH Zürich) · John Guttag (Massachusetts Institute of Technology) · Mert Sabuncu (Cornell)

Fast Low-rank Metric Learning for Large-scale and High-dimensional Data
Han Liu (Tsinghua University) · Zhizhong Han (University of Maryland, College Park) · Yu-Shen Liu (Tsinghua University) · Ming Gu (Tsinghua University)

Efficient Symmetric Norm Regression via Linear Sketching
Zhao Song (University of Washington) · Ruosong Wang (Carnegie Mellon University) · Lin Yang (Johns Hopkins University) · Hongyang Zhang (Carnegie Mellon University) · Peilin Zhong (Columbia University)

RUBi: Reducing Unimodal Biases in Visual Question Answering
Remi Cadene (Sorbonne University - LIP6) · Corentin Dancette (Sorbonne Université) · Hedi Ben younes (Université Pierre & Marie Curie / Heuritech) · Matthieu Cord (Sorbonne University) · Devi Parikh (Georgia Tech / Facebook AI Research (FAIR))

Reducing Scene Bias of Convolutional Neural Networks for Human Action Understanding
Jinwoo Choi (Virginia Tech) · Chen Gao (Virginia Tech) · Joseph C. E. Messou (Virginia Tech) · Jia-Bin Huang (Virginia Tech)

NeurVPS: Neural Vanishing Point Scanning via Conic Convolution
Yichao Zhou (UC Berkeley) · Haozhi Qi (UC Berkeley) · Jingwei Huang (Stanford University) · Yi Ma (UC Berkeley)

DATA: Differentiable ArchiTecture Approximation
Jianlong Chang (National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences) · xinbang zhang (Institute of Automation,Chinese Academy of Science) · Yiwen Guo (Intel Labs China) · GAOFENG MENG (Institute of Automation, Chinese Academy of Sciences) · SHIMING XIANG (Chinese Academy of Sciences, China) · Chunhong Pan (Institute of Automation, Chinese Academy of Sciences)

Learn, Imagine and Create: Text-to-Image Generation from Prior Knowledge
Tingting Qiao (Zhejiang University) · Jing Zhang (The University of Sydney) · Duanqing Xu (Zhejiang University) · Dacheng Tao (University of Sydney)

Memory-oriented Decoder for Light Field Salient Object Detection
Miao Zhang (Dalian University of Technology) · Jingjing Li (Dalian University of Technology) · Wei Ji (Dalian University of Technology) · Yongri Piao (Dalian University of Technology) · Huchuan Lu (Dalian University of Technology)

Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition
Xuesong Niu (Institute of Computing Technology, CAS) · Hu Han (ICT, CAS) · Shiguang Shan (Chinese Academy of Sciences) · Xilin Chen (Institute of Computing Technology, Chinese Academy of Sciences)

Correlated Uncertainty for Learning Dense Correspondences from Noisy Labels
Natalia Neverova (Facebook AI Research) · David Novotny (Facebook AI Research) · Andrea Vedaldi (University of Oxford / Facebook AI Research)

Powerset Convolutional Neural Networks
Chris Wendler (ETH Zurich) · Markus Püschel (ETH Zurich) · Dan Alistarh (IST Austria)

Optimal Pricing in Repeated Posted-Price Auctions with Different Patience of the Seller and the Buyer
Arsenii Vanunts (Yandex) · Alexey Drutsa (Yandex)

An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums
Hadrien Hendrikx (INRIA) · Francis Bach (INRIA - Ecole Normale Superieure) · Laurent Massoulié (Inria)

Efficient 3D Deep Learning via Point-Based Representation and Voxel-Based Convolution
Zhijian Liu (MIT) · Haotian Tang (Shanghai Jiao Tong University) · Yujun Lin (MIT) · Song Han (MIT)

Deep Learning without Weight Transport
Mohamed Akrout (University of Toronto) · Collin Wilson (University of Toronto) · Peter Humphreys (Deepmind) · Timothy Lillicrap (DeepMind & UCL) · Douglas Tweed (University of Toronto)

Combinatorial Bandits with Relative Feedback
Aadirupa Saha (Indian Institute of Science) · Aditya Gopalan (Indian Institute of Science)

General Proximal Incremental Aggregated Gradient Algorithms: Better and Novel Results under General Scheme
Tao Sun (National university of defense technology) · Yuejiao Sun (University of California, Los Angeles) · Dongsheng Li (School of Computer Science, National University of Defense Technology) · Qing Liao (Harbin Institute of Technology (Shenzhen))

Joint Optimizing of Cycle-Consistent Networks
Leonidas J Guibas (stanford.edu) · Qixing Huang (The University of Texas at Austin) · Zhenxiao Liang (The University of Texas at Austin)

Explicit Disentanglement of Appearance and Perspective in Generative Models
Nicki Skafte Detlefsen (Technical University of Denmark) · Søren Hauberg (Technical University of Denmark)

Polynomial Cost of Adaptation for X-Armed Bandits
Hedi Hadiji (Laboratoire de Mathematiques d’Orsay, Univ. Paris-Sud,)

Learning to Propagate for Graph Meta-Learning
LU LIU (University of Technology Sydney) · Tianyi Zhou (University of Washington, Seattle) · Guodong Long (University of Technology Sydney) · Jing Jiang (University of Technology Sydney) · Chengqi Zhang (University of Technology Sydney)

Secretary Ranking with Minimal Inversions
Sepehr Assadi (Princeton University) · Eric Balkanski (Harvard University) · Renato Leme (Google Research)

Nonparametric Regressive Point Processes Based on Conditional Gaussian Processes
Siqi Liu (University of Pittsburgh) · Milos Hauskrecht (University of Pittsburgh)

Learning Perceptual Inference by Contrasting
Chi Zhang (University of California, Los Angeles) · Baoxiong Jia (UCLA) · Feng Gao (UCLA) · Yixin Zhu (University of California, Los Angeles) · HongJing Lu (UCLA) · Song-Chun Zhu (UCLA)

Selecting the independent coordinates of manifolds with large aspect ratios
Yu-Chia Chen (University of Washington) · Marina Meila (University of Washington)

Region-specific Diffeomorphic Metric Mapping
Zhengyang Shen (University of North Carolina at Chapel Hill) · Francois-Xavier Vialard (University Paris-Est) · Marc Niethammer (UNC Chapel Hill)

Subset Selection via Supervised Facility Location
Chengguang Xu (Northeastern University) · Ehsan Elhamifar (Northeastern University)

Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations
Vincent Sitzmann (Stanford University) · Michael Zollhoefer (Facebook Reality Labs) · Gordon Wetzstein (Stanford University)

Reconciling λ-Returns with Experience Replay
Brett Daley (Northeastern University) · Christopher Amato (Northeastern University)

Control Batch Size and Learning Rate to Generalize Well: Theoretical and Empirical Evidence
Fengxiang He (The University of Sydney) · Tongliang Liu (The University of Sydney) · Dacheng Tao (University of Sydney)

Non-Asymptotic Gap-Dependent Regret Bounds for Tabular MDPs
Max Simchowitz (Berkeley) · Kevin Jamieson (U Washington)

A Graph Theoretic Framework of Recomputation Algorithms for Memory-Efficient Backpropagation
Mitsuru Kusumoto (Preferred Networks, Inc.) · Takuya Inoue (University of Tokyo) · Gentaro Watanabe (Preferred Networks, Inc.) · Takuya Akiba (Preferred Networks, Inc.) · Masanori Koyama (Preferred Networks Inc. )

Combinatorial Inference against Label Noise
Paul Hongsuck Seo (POSTECH) · Geeho Kim (Seoul National University) · Bohyung Han (Seoul National University)

Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning
Chao Qu (Ant Financial Services Group) · Shie Mannor (Technion) · Huan Xu (Georgia Inst. of Technology) · Yuan Qi (Ant Financial Services Group) · Le Song (Ant Financial Services Group) · Junwu Xiong (Ant Financial Services Group)

Convolution with even-sized kernels and symmetric padding
Shuang Wu (Tsinghua University) · Guanrui Wang (Tsinghua University) · Pei Tang (Tsinghua University) · Feng Chen (Tsinghua University) · Luping Shi (tsinghua university)

On The Classification-Distortion-Perception Tradeoff
Dong Liu (University of Science and Technology of China) · Haochen Zhang (University of Science and Technology of China) · Zhiwei Xiong (University of Science and Technology of China)

Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up
Dominic Richards (University of Oxford) · Patrick Rebeschini (University of Oxford)

Online sampling from log-concave distributions
Holden Lee (Princeton University) · Oren Mangoubi (Worcester Polytechnic Institute) · Nisheeth Vishnoi (Yale University)

Envy-Free Classification
Maria-Florina Balcan (Carnegie Mellon University) · Travis Dick (Carnegie Mellon University) · Ritesh Noothigattu (Carnegie Mellon University) · Ariel Procaccia (Carnegie Mellon University)

Finding Friend and Foe in Multi-Agent Games
Jack S Serrino (MIT) · Max Kleiman-Weiner (Harvard/MIT) · David Parkes (Harvard University) · Josh Tenenbaum (MIT)

Computer Vision with a Single (Robust) Classifier
Shibani Santurkar (MIT) · Andrew Ilyas (MIT) · Dimitris Tsipras (MIT) · Logan Engstrom (MIT) · Brandon Tran (Massachusetts Institute of Technology) · Aleksander Madry (MIT)

Gated CRF Loss for Weakly Supervised Semantic Image Segmentation
Anton Obukhov (ETH Zurich) · Stamatios Georgoulis (ETH Zurich) · Dengxin Dai (ETH Zurich) · Luc V Gool (Computer Vision Lab, ETH Zurich)

Model Compression with Adversarial Robustness: A Unified Optimization Framework
Shupeng Gui (University of Rochester) · Haotao N Wang (Texas A&M University) · Haichuan Yang (University of Rochester) · Chen Yu (University of Rochester) · Zhangyang Wang (TAMU) · Ji Liu (University of Rochester, Tencent AI lab)

Neuron Communication Networks
Jianwei Yang (Georgia Tech) · Zhile Ren (Georgia Tech) · Chuang Gan (MIT-IBM Watson AI Lab) · Hongyuan Zhu (Astar) · Ji Lin (MIT) · Devi Parikh (Georgia Tech / Facebook AI Research (FAIR))

CondConv: Conditionally Parameterized Convolutions for Efficient Inference
Brandon Yang (Google Brain) · Gabriel Bender (Google Brain) · Quoc V Le (Google) · Jiquan Ngiam (Google Brain)

Regression Planning Networks
Danfei Xu (Stanford University) · Roberto Martín-Martín (Stanford University) · De-An Huang (Stanford University) · Yuke Zhu (Stanford University) · Silvio Savarese (Stanford University) · Li Fei-Fei (Stanford University)

Twin Auxilary Classifiers GAN
Mingming Gong (University of Melbourne) · Yanwu Xu (University of Pittsburgh) · Chunyuan Li (Microsoft Research) · Kun Zhang (CMU) · Kayhan Batmanghelich (University of Pittsburgh)

Conditional Structure Generation through Graph Variational Generative Adversarial Nets
Carl Yang (University of Illinois, Urbana Champaign) · Peiye Zhuang (UIUC) · Wenhan Shi (UIUC) · Alan Luu (UIUC) · Pan Li (Stanford)

Distributional Policy Optimization: An Alternative Approach for Continuous Control
Chen Tessler (Technion) · Guy Tennenholtz (Technion) · Shie Mannor (Technion)

Sampling Sketches for Concave Sublinear Functions of Frequencies
Edith Cohen (Google) · Ofir Geri (Stanford University)

Deliberative Explanations: visualizing network insecurities
Pei Wang (UC San Diego) · Nuno Nvasconcelos (UC San Diego)

Computing Full Conformal Prediction Set with Approximate Homotopy
Eugene Ndiaye (Riken AIP) · Ichiro Takeuchi (Nagoya Institute of Technology)

Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift
Stephan Rabanser (Amazon / TU Munich) · Stephan Günnemann (Technical University of Munich) · Zachary Lipton (Carnegie Mellon University)

Hierarchical Reinforcement Learning with Advantage-Based Auxiliary Rewards
Siyuan Li (Tsinghua University) · Rui Wang (Stanford University) · Minxue Tang (Tsinghua University) · Chongjie Zhang (Tsinghua University)

Multi-View Reinforcement Learning
Minne Li (University College London) · Lisheng Wu (UCL) · Jun WANG (UCL)

Cascade RPN: Delving into High-Quality Region Proposal Network with Adaptive Convolution
Thang Vu (KAIST) · Hyunjun Jang (KAIST) · Trung X Pham (KAIST) · Chang Yoo (KAIST)

Neural Diffusion Distance for Image Segmentation
Jian Sun (Xi'an Jiaotong University) · Zongben Xu (XJTU)

Fine-grained Optimization of Deep Neural Networks
Mete Ozay (Independent Researcher (N/A))

Extending Stein’s Unbiased Risk Estimator To Train Deep Denoisers with Correlated Pairs of Noisy Images
Magauiya Zhussip (UNIST) · Shakarim Soltanayev (Ulsan National Institute of Science and Technology) · Se Young Chun (UNIST)

Wibergian Learning of Continuous Energy Functions
Chris Russell (The Alan Turing Institute/ The University of Surrey) · Matteo Toso (University of Surrey) · Neill Campbell (University of Bath)

Hyperspherical Prototype Networks
Pascal Mettes (University of Amsterdam) · Elise van der Pol (University of Amsterdam) · Cees Snoek (University of Amsterdam)

Expressive power of tensor-network factorizations for probabilistic modelling
Ivan Glasser (Max Planck Institute of Quantum Optics) · Ryan Sweke (Freie Universitaet Berlin) · Nicola Pancotti (Max Planck Institute of Quantum Optics) · Jens Eisert (Freie Universitaet Berlin) · Ignacio Cirac (Max-Planck Institute of Quantum Optics)

HyperGCN: A New Method For Training Graph Convolutional Networks on Hypergraphs
Naganand Yadati (Indian Institute of Science) · Madhav Nimishakavi (Indian Institute of Science) · Prateek Yadav (Indian Institute of Science) · Vikram Nitin (Indian Institute of Science) · Anand Louis (Indian Institute of Science, Bangalore, India) · Partha Talukdar (Indian Institute of Science, Bangalore)

SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points
Zhize Li (Tsinghua University)

Efficient Meta Learning via Minibatch Proximal Update
Pan Zhou (National University of Singapore) · Xiaotong Yuan (Nanjing University of Information Science & Technology) · Huan Xu (Alibaba Group) · Shuicheng Yan (National University of Singapore) · Jiashi Feng (National University of Singapore)

Unconstrained Monotonic Neural Networks
Antoine Wehenkel (ULiège) · Gilles Louppe (University of Liège)

Guided Similarity Separation for Image Retrieval
Chundi Liu (Layer6 AI) · Guangwei Yu (Layer6) · Maksims Volkovs (Layer6 AI) · Cheng Chang (Layer6 AI) · Himanshu Rai (Layer6 AI) · Junwei Ma (Layer6 AI) · Satya Krishna Gorti (Layer6 AI)

Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
Kaidi Cao (Stanford University) · Colin Wei (Stanford University) · Adrien Gaidon (Toyota Research Institute) · Nikos Arechiga (Toyota Research Institute) · Tengyu Ma (Stanford)

Strategizing against No-regret Learners
Yuan Deng (Duke University) · Jon Schneider (Google Research) · Balasubramanian Sivan (Google Research)

D-VAE: A Variational Autoencoder for Directed Acyclic Graphs
Muhan Zhang (Washington University; Facebook (now)) · Shali Jiang (Washington University in St. Louis) · Zhicheng Cui (Washington University in St. Louis) · Roman Garnett (Washington University in St. Louis) · Yixin Chen (Washington University in St. Louis)

Hierarchical Optimal Transport for Document Representation
Mikhail Yurochkin (IBM Research, MIT-IBM Watson AI Lab) · Sebastian Claici (MIT) · Edward Chien (Massachusetts Institute of Technology) · Farzaneh Mirzazadeh (MIT-IBM Watson AI Lab, IBM Research) · Justin M Solomon (MIT)

Multivariate Sparse Coding of Nonstationary Covariances with Gaussian Processes
Rui Li (Rochester Institute of Technology)

Positional Normalization
Boyi Li (Cornell University) · Felix Wu (Cornell University) · Kilian Weinberger (Cornell University / ASAPP Research) · Serge Belongie (Cornell University)

A New Defense Against Adversarial Images: Turning a Weakness into a Strength
Shengyuan Hu (Cornell University) · Tao Yu (Cornell University) · Chuan Guo (Cornell University) · Wei-Lun Chao (Cornell University Ohio State University (OSU)) · Kilian Weinberger (Cornell University / ASAPP Research)

Quadratic Video Interpolation
Xiangyu Xu (Carnegie Mellon University) · Li Siyao (SenseTime Research) · Wenxiu Sun (SenseTime Research) · Qian Yin (Beijing Normal University) · Ming-Hsuan Yang (Google / UC Merced)

ResNets Ensemble via the Feynman-Kac Formalism to Improve Natural and Robust Accuracies
Bao Wang (UCLA) · Zuoqiang Shi (zqshi@mail.tsinghua.edu.cn) · Stanley Osher (UCLA)

Incremental Scene Synthesis
Benjamin Planche (Siemens Corporate Technology) · Xuejian Rong (City University of New York) · Ziyan Wu (United Imaging Intelligence) · Srikrishna Karanam (United Imaging Intelligence) · Harald Kosch (PASSAU) · YingLi Tian (City University of New York) · Jan Ernst (Siemens Research) · ANDREAS HUTTER (Siemens Corporate Technology, Germany)

Self-Supervised Generalisation with Meta Auxiliary Learning
Shikun Liu (Imperial College London) · Andrew Davison (Imperial College London) · Edward Johns (Imperial College London)

Variational Denoising Network: Toward Blind Noise Modeling and Removal
Zongsheng Yue (Xi'an Jiaotong University) · Hongwei Yong (The Hong Kong Polytechnic University) · Qian Zhao (Xi'an Jiaotong University) · Deyu Meng (Xi'an Jiaotong University) · Lei Zhang (The Hong Kong Polytechnic Univ)

Fast Sparse Group Lasso
Yasutoshi Ida (NTT) · Yasuhiro Fujiwara (NTT Communication Science Laboratories) · Hisashi Kashima (Kyoto University/RIKEN Center for AIP)

Learnable Tree Filter for Structure-preserving Feature Transform
Lin Song (Xi'an Jiaotong University) · Yanwei Li (Institute of Automation, Chinese Academy of Sciences) · Zeming Li (Megvii(Face++) Inc) · Gang Yu (Megvii Inc) · Hongbin Sun (Xi'an Jiaotong University) · Jian Sun (Megvii, Face++) · Nanning Zheng (Xi'an Jiaotong University)

Data-Dependence of Plateau Phenomenon in Learning with Neural Network --- Statistical Mechanical Analysis
Yuki Yoshida (The University of Tokyo) · Masato Okada (The University of Tokyo)

Coordinated hippocampal-entorhinal replay as structural inference
Talfan Evans (University College London) · Neil Burgess (University College London)

Cascaded Dilated Dense Network with Two-step Data Consistency for MRI Reconstruction
Hao Zheng (East China Normal University) · Faming Fang (East China Normal University) · Guixu Zhang (East China Normal University)

On the Ineffectiveness of Variance Reduced Optimization for Deep Learning
Aaron Defazio (Facebook AI Research) · Leon Bottou (FAIR)

On the Curved Geometry of Accelerated Optimization
Aaron Defazio (Facebook AI Research)

Multi-marginal Wasserstein GAN
Jiezhang Cao (South China University of Technology) · Langyuan Mo (South China University of Technology) · Yifan Zhang (South China University of Technology) · Kui Jia (South China University of Technology) · Chunhua Shen (University of Adelaide) · Mingkui Tan (South China University of Technology)

Better Exploration with Optimistic Actor Critic
Kamil Ciosek (Microsoft) · Quan Vuong (University of California San Diego) · Robert Loftin (Microsoft Research) · Katja Hofmann (Microsoft Research)

Importance Resampling for Off-policy Prediction
Matthew Schlegel (University of Alberta) · Wesley Chung (McGill University) · Daniel Graves (Huawei Technologies Canada) · Jian Qian (University of Alberta) · Martha White (University of Alberta)

The Label Complexity of Active Learning from Observational Data
Songbai Yan (University of California, San Diego) · Kamalika Chaudhuri (UCSD) · Tara Javidi (University of California San Diego)

Meta-Learning Representations for Continual Learning
Khurram Javed (University of Alberta) · Martha White (University of Alberta)

Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training
Haichao Zhang (Horizon Robotics) · Jianyu Wang (Baidu USA)

Visualizing the PHATE of Neural Networks
Scott Gigante (Yale University) · Adam S Charles (Princeton University) · Smita Krishnaswamy (Yale University) · Gal Mishne (UC San Diego)

The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers
Alex Lu (University of Toronto) · Amy Lu (University of Toronto/Vector Institute) · Wiebke Schormann (Sunnybrook Research Institute) · David Andrews (Sunnybrook Research Institute) · Alan Moses (University of Toronto)

Nonconvex Low-Rank Tensor Completion from Noisy Data
Changxiao Cai (Princeton University) · Gen Li (Tsinghua University) · H. Vincent Poor (Princeton University) · Yuxin Chen (Princeton University)

Beyond Online Balanced Descent: An Optimal Algorithm for Smoothed Online Optimization
Gautam Goel (Caltech) · Yiheng Lin (Institute for Interdisciplinary Information Sciences, Tsinghua University) · Haoyuan Sun (California Institute of Technology) · Adam Wierman (California Institute of Technology)

Channel Gating Neural Networks
Weizhe Hua (Cornell University) · Yuan Zhou (Cornell) · Christopher De Sa (Cornell) · Zhiru Zhang (Cornell Univeristy) · G. Edward Suh (Cornell University)

Neural networks grown and self-organized by noise
Guruprasad Raghavan (California Institute of Technology) · Matt Thomson (California Institute of Technology)

Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning
Xinyang Chen (Tsinghua University) · Sinan Wang (Tsinghua University) · Bo Fu (Tsinghua University) · Mingsheng Long (Tsinghua University) · Jianmin Wang (Tsinghua University)

Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting
Jun Shu (Xi'an Jiaotong University) · Qi Xie (Xi'an Jiaotong University) · Lixuan Yi (Xi'an Jiaotong University) · Qian Zhao (Xi'an Jiaotong University) · Sanping Zhou (Xi'an Jiaotong University) · Zongben Xu (Xi'an Jiaotong University) · Deyu Meng (Xi'an Jiaotong University)

Variational Structured Semantic Inference for Diverse Image Captioning
Fuhai Chen (Xiamen University) · Rongrong Ji (Xiamen University, China) · Jiayi Ji (Xiamen University) · Xiaoshuai Sun (Xiamen University) · Baochang Zhang (Beihang University) · Xuri Ge (Xiamen University) · Yongjian Wu (Tencent Technology (Shanghai) Co.,Ltd) · Feiyue Huang (Tencent) · Yan Wang (Microsoft)

Mapping State Space using Landmarks for Universal Goal Reaching
Zhiao Huang (University of California San Diego) · Hao Su (University of California San Diego) · Fangchen Liu (University of California, San Diego)

Transferable Normalization: Towards Improving Transferability of Deep Neural Networks
Ximei Wang (Tsinghua University) · Ying Jin (Tsinghua University) · Mingsheng Long (Tsinghua University) · Jianmin Wang (Tsinghua University) · Michael Jordan (UC Berkeley)

Random deep neural networks are biased towards simple functions
Giacomo De Palma (MIT) · Bobak Kiani (Massachusetts Institute of Technology) · Seth Lloyd (MIT)

XNAS: Neural Architecture Search with Expert Advice
Niv Nayman (Alibaba Group) · Asaf Noy (Alibaba) · Tal Ridnik (MIIL Alibaba) · Itamar Friedman (Alibaba) · Jing Rong (Alibaba) · Lihi Zelnik (Alibaba)

CNN^{2}: Viewpoint Generalization via a Binocular Vision
Wei-Da Chen (National Tsing Hua University) · Shan-Hung (Brandon) Wu (National Tsing Hua University)

Generalized Off-Policy Actor-Critic
Shangtong Zhang (University of Oxford) · Wendelin Boehmer (University of Oxford) · Shimon Whiteson (University of Oxford)

DAC: The Double Actor-Critic Architecture for Learning Options
Shangtong Zhang (University of Oxford) · Shimon Whiteson (University of Oxford)

Numerically Accurate Hyperbolic Embeddings Using Tiling-Based Models
Tao Yu (Cornell University) · Christopher De Sa (Cornell)

Controlling Neural Level Sets
Matan Atzmon (Weizmann Institute Of Science) · Niv Haim (Weizmann Institute of Science) · Lior Yariv (Weizmann Institute of Science) · Ofer Israelov (Weizmann Institute of Science) · Haggai Maron (NVIDIA Research) · Yaron Lipman (Weizmann Institute of Science)

Blended Matching Pursuit
Cyrille Combettes (Georgia Institute of Technology) · Sebastian Pokutta (Georgia Institute of Technology)

An Improved Analysis of Training Over-parameterized Deep Neural Networks
Difan Zou (University of California, Los Angeles) · Quanquan Gu (UCLA)

Controllable Text to Image Generation
Bowen Li (University of Oxford) · Xiaojuan Qi (University of Oxford) · Thomas Lukasiewicz (University of Oxford) · Philip Torr (University of Oxford)

Improving Textual Network Learning with Variational Homophilic Embeddings
Wenlin Wang (Duke Univeristy) · Chenyang Tao (Duke University) · Zhe Gan (Microsoft) · Guoyin Wang (Duke University) · Liqun Chen (Duke University) · Xinyuan Zhang (Duke University) · Ruiyi Zhang (Duke University) · Qian Yang (Duke University) · Ricardo Henao (Duke University) · Lawrence Carin (Duke University)

Rethinking Generative Coverage: A Pointwise Guaranteed Approach
Peilin Zhong (Columbia University) · Yuchen Mo (Columbia University) · Chang Xiao (Columbia University) · Pengyu Chen (Columbia University) · Changxi Zheng (Columbia University)

The Randomized Midpoint Method for Log-Concave Sampling
Ruoqi Shen (University of Washington) · Yin Tat Lee (UW)

Sample-Efficient Deep Reinforcement Learning via Episodic Backward Update
Su Young Lee (KAIST) · Choi Sungik (KAIST) · Sae-Young Chung (KAIST)

Fully Neural Network based Model for General Temporal Point Processes
Takahiro Omi (The University of Tokyo & RIKEN AIP) · naonori ueda (RIKEN AIP) · Kazuyuki Aihara (The University of Tokyo)

Gate Decorator: Global Filter Pruning Method for Accelerating Deep Convolutional Neural Networks
Zhonghui You (Peking University) · Kun Yan (Peking University) · Jinmian Ye (SMILE Lab) · Meng Ma (Peking University) · Ping Wang (Peking University)

Discrimination in Online Markets: Effects of Social Bias on Learning from Reviews and Policy Design
Faidra Georgia Monachou (Stanford University) · Itai Ashlagi (Stanford)

Provably Powerful Graph Networks
Haggai Maron (NVIDIA Research) · Heli Ben-Hamu (Weizmann Institute of Science) · Hadar Serviansky (Weizmann Institute of Sciences) · Yaron Lipman (Weizmann Institute of Science)

Order Optimal One-Shot Distributed Learning
Arsalan Sharifnassab (Sharif University of Technology) · Saber Salehkaleybar (Sharif University of Technology) · S. Jamaloddin Golestani (Sharif University of Technology)

Information Competing Process for Learning Diversified Representations
Jie Hu (Xiamen University) · Rongrong Ji (Xiamen University, China) · ShengChuan Zhang (Xiamen University) · Xiaoshuai Sun (Xiamen University) · Qixiang Ye (University of Chinese Academy of Sciences, China) · Chia-Wen Lin (National Tsing Hua University) · Qi Tian (Huawei Noah’s Ark Lab)

GENO -- GENeric Optimization for Classical Machine Learning
Soeren Laue (Friedrich Schiller University Jena / Data Assessment Solutions) · Matthias Mitterreiter (Friedrich Schiller University Jena) · Joachim Giesen (Friedrich-Schiller-Universitat Jena)

Conditional Independence Testing using Generative Adversarial Networks
Alexis Bellot (University of Cambridge / Alan Turing Institute) · Mihaela van der Schaar (University of Cambridge, Alan Turing Institute and UCLA)

Online Stochastic Shortest Path with Bandit Feedback and Unknown Transition Function
Aviv Rosenberg (Tel Aviv University) · Yishay Mansour (Tel Aviv University / Google)

Partitioning Structure Learning for Segmented Linear Regression Trees
Xiangyu Zheng (Peking University) · Song Xi Chen (Peking University)

A Tensorized Transformer for Language Modeling
Xindian Ma (Tianjin University) · Peng Zhang (Tianjin University) · Shuai Zhang (Tianjin University) · Nan Duan (Microsoft Research Asia) · Yuexian Hou (Tianjin University) · Ming Zhou (Microsoft Research) · Dawei Song (Beijing Institute of Technology)

Kernel Stein Tests for Multiple Model Comparison
Jen Ning Lim (Max Planck Institute for Intelligent Systems) · Makoto Yamada (Kyoto University / RIKEN AIP) · Bernhard Schölkopf (MPI for Intelligent Systems) · Wittawat Jitkrittum (Max Planck Institute for Intelligent Systems)

Disentangled behavioural representations
Amir Dezfouli (Data61, CSIRO) · Hassan Ashtiani (McMaster University) · Omar Ghattas (University of Chicago) · Richard Nock (Data61, the Australian National University and the University of Sydney) · Peter Dayan (Max Planck Institute for Biological Cybernetics) · Cheng Soon Ong (Data61 and ANU)

More Is Less: Learning Efficient Video Representations by Temporal Aggregation Module
Quanfu Fan (IBM Research) · Chun-Fu (Richard) Chen (IBM Research) · Hilde Kuehne (University of Bonn) · Marco Pistoia (IBM Research) · David Cox (MIT-IBM Watson AI Lab)

Rethinking the CSC Model for Natural Images
Dror Simon (Technion) · Michael Elad (Technion)

Integrating Generative and Discriminative Sparse Kernel Machines for Multi-class Active Learning
Weishi Shi (Rochester Institute of Technology) · Qi Yu (Rochester Institute of Technology)

Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity
Deepak Pathak (UC Berkeley, FAIR, CMU) · Christopher Lu (UC Berkeley and Covariant.ai) · Trevor Darrell (UC Berkeley) · Phillip Isola (Massachusetts Institute of Technology) · Alexei Efros (UC Berkeley)

Perceiving the arrow of time in autoregressive motion
Kristof Meding (University Tübingen) · Dominik Janzing (Amazon) · Bernhard Schölkopf (MPI for Intelligent Systems) · Felix A. Wichmann (University of Tübingen)

DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections
Ofir Nachum (Google Brain) · Yinlam Chow (DeepMind) · Bo Dai (Google Brain) · Lihong Li (Google Brain)

Hyper-Graph-Network Decoders for Block Codes
Eliya Nachmani (Tel Aviv University and Facebook AI Research) · Lior Wolf (Facebook AI Research)

Large Scale Markov Decision Processes with Changing Rewards
Adrian Rivera Cardoso (Georgia Tech) · He Wang (Georgia Institute of Technology) · Huan Xu (Georgia Inst. of Technology)

Multiview Aggregation for Learning Category-Specific Shape Reconstruction
Srinath Sridhar (Stanford University) · Davis Rempe (Stanford University) · Julien Valentin (Google) · Bouaziz Sofien () · Leonidas J Guibas (stanford.edu)

Semi-Parametric Dynamic Contextual Pricing
Virag Shah (Stanford) · Ramesh Johari (Stanford University) · Jose Blanchet (Stanford University)

Nearly Linear-Time, Deterministic Algorithm for Maximizing (Non-Monotone) Submodular Functions Under Cardinality Constraint
Alan Kuhnle (Florida State University)

Initialization of ReLUs for Dynamical Isometry
Rebekka Burkholz (Harvard University) · Alina Dubatovka (ETH Zurich)

Gradient Information for Representation and Modeling
Jie Ding (University of Minnesota) · Robert Calderbank (Duke University) · Vahid Tarokh (Duke University)

SpiderBoost and Momentum: Faster Variance Reduction Algorithms
Zhe Wang (Ohio State University) · Kaiyi Ji (The Ohio State University) · Yi Zhou (University of Utah) · Yingbin Liang (The Ohio State University) · Vahid Tarokh (Duke University)

Minimax rates of estimating approximate differential privacy
Xiyang Liu (University of Washington) · Sewoong Oh (University of Washington)

Backprop with Approximate Activations for Memory-efficient Network Training
Ayan Chakrabarti (Washington University in St. Louis) · Benjamin Moseley (Carnegie Mellon University)

Training Image Estimators without Image Ground Truth
Zhihao Xia (Washington University in St. Louis) · Ayan Chakrabarti (Washington University in St. Louis)

Deep Structured Prediction for Facial Landmark Detection
Lisha Chen (Rensselaer Polytechnic Institute) · Hui Su (IBM) · Qiang Ji (Rensselaer Polytechnic Institute)

Information-Theoretic Confidence Bounds for Reinforcement Learning
Xiuyuan Lu (Stanford University) · Benjamin Van Roy (Stanford University)

Transfer Anomaly Detection by Inferring Latent Domain Representations
Atsutoshi Kumagai (NTT) · Tomoharu Iwata (NTT) · Yasuhiro Fujiwara (NTT Communication Science Laboratories)

Total Least Squares Regression in Input Sparsity Time
Huaian Diao (Northeast Normal University) · Zhao Song (Harvard University & University of Washington) · David Woodruff (Carnegie Mellon University) · Xin Yang (University of Washington)

Park: An Open Platform for Learning-Augmented Computer Systems
Hongzi Mao (MIT) · Parimarjan Negi (MIT CSAIL) · Akshay Narayan (MIT CSAIL) · Hanrui Wang (Massachusetts Institute of Technology) · Jiacheng Yang (MIT CSAIL) · Haonan Wang (MIT CSAIL) · Ryan Marcus (MIT CSAIL) · ravichandra addanki (Massachusetts Institute of Technology) · Mehrdad Khani Shirkoohi (MIT) · Songtao He (Massachusetts Institute of Technology) · Vikram Nathan (MIT) · Frank Cangialosi (MIT CSAIL) · Shaileshh Venkatakrishnan (MIT) · Wei-Hung Weng (MIT) · Song Han (MIT) · Tim Kraska (MIT) · Dr.Mohammad Alizadeh (Massachusetts institute of technology)

Adapting Neural Networks for the Estimation of Treatment Effects
Claudia Shi (Columbia University) · David Blei (Columbia University) · Victor Veitch (Columbia University)

Learning Transferable Graph Exploration
Hanjun Dai (Georgia Tech) · Yujia Li (DeepMind) · Chenglong Wang (University of Washington) · Rishabh Singh (Google Brain) · Po-Sen Huang (DeepMind) · Pushmeet Kohli (DeepMind)

Conformal Prediction Under Covariate Shift
Rina Foygel Barber (University of Chicago) · Emmanuel Candes (Stanford University) · Aaditya Ramdas (CMU) · Ryan Tibshirani (Carnegie Mellon University)

Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation
Chen Dan (Carnegie Mellon University) · Hong Wang (Massachusetts Institute of Technology) · Hongyang Zhang (Carnegie Mellon University) · Yuchen Zhou (University of Wisconsin, Madison) · Pradeep Ravikumar (Carnegie Mellon University)

Asymmetric Valleys: Beyond Sharp and Flat Local Minima
Haowei He (Beihang University) · Gao Huang (Tsinghua) · Yang Yuan (Cornell University)

Positive-Unlabeled Compression on the Cloud
Yixing Xu (Huawei Noah's Ark Lab) · Yunhe Wang (Huawei Noah's Ark Lab) · Hanting Chen (Peking University) · Kai Han (Huawei Noah's Ark Lab) · Chunjing XU (Huawei Technologies) · Dacheng Tao (University of Sydney) · Chang Xu (University of Sydney)

Direct Estimation of Differential Functional Graphical Model
Boxin Zhao (UChicago) · Sam Wang (UW) · Mladen Kolar (University of Chicago)

On the Calibration of Multiclass Classification with Rejection
Chenri Ni (The University of Tokyo) · Nontawat Charoenphakdee (The University of Tokyo / RIKEN) · Junya Honda (The University of Tokyo / RIKEN) · Masashi Sugiyama (RIKEN / University of Tokyo)

Third-Person Visual Imitation Learning via Decoupled Hierarchical Control
Pratyusha Sharma (Carnegie Mellon University) · Deepak Pathak (UC Berkeley, FAIR, CMU) · Abhinav Gupta (Facebook AI Research/CMU)

Stagewise Training Accelerates Convergence of Testing Error Over SGD
Zhuoning Yuan (University of Iowa) · Yan Yan (the University of Iowa) · Jing Rong (Alibaba) · Tianbao Yang (The University of Iowa)

Learning Robust Options by Conditional Value at Risk Optimization
Takuya Hiraoka (NEC / AIST / RIKEN-AIP) · Takahisa Imagawa (National Institute of Advanced Industrial Science and Technology) · Tatsuya Mori (NEC) · Takashi Onishi (NEC) · Yoshimasa Tsuruoka (The University of Tokyo)

Non-asymptotic Analysis of Stochastic Methods for Non-Smooth Non-Convex Regularized Problems
Yi Xu (The University of Iowa) · Jing Rong (Alibaba) · Tianbao Yang (The University of Iowa)

On Learning Over-parameterized Neural Networks: A Functional Approximation Prospective
Lili Su (MIT) · Pengkun Yang (Princeton University)

Drill-down: Interactive Retrieval of Complex Scenes using Natural Language Queries
Fuwen Tan (University of Virginia) · Paola Cascante-Bonilla (University of Virginia) · Xiaoxiao Guo (IBM Research) · Hui Wu (IBM Research) · Song Feng (IBM Research) · Vicente Ordonez (University of Virginia)

Visual Sequence Learning in Hierarchical Prediction Networks and Primate Visual Cortex
JIELIN QIU (Shanghai Jiao Tong University) · Ge Huang (Carnegie Mellon University) · Tai Sing Lee (Carnegie Mellon University)

Dual Variational Generation for Low Shot Heterogeneous Face Recognition
Chaoyou Fu (Institute of Automation, Chinese Academy of Sciences) · Xiang Wu (Institue of Automation, Chinese Academy of Science) · Yibo Hu (Institute of Automation, Chinese Academy of Sciences) · Huaibo Huang (Institute of Automation, Chinese Academy of Science) · Ran He (NLPR, CASIA)

Discovering Neural Wirings
Mitchell Wortsman (University of Washington, Allen Institute for Artificial Intelligence) · Ali Farhadi (University of Washington, Allen Institute for Artificial Intelligence) · Mohammad Rastegari (XNOR.AI- AI2)

On the Optimality of Perturbations in Stochastic and Adversarial Multi-armed Bandit Problems
Baekjin Kim (University of Michigan) · Ambuj Tewari (University of Michigan)

Knowledge Extraction with No Observable Data
Jaemin Yoo (Seoul National University) · Minyong Cho (Seoul National University) · Taebum Kim (Seoul National University) · U Kang (Seoul National University)

PAC-Bayes under potentially heavy tails
Matthew Holland (Osaka University)

One-Shot Object Detection with Co-Attention and Co-Excitation
Ting-I Hsieh (National Tsing Hua University) · Yi-Chen Lo (National Tsing Hua University) · Hwann-Tzong Chen (National Tsing Hua University) · Tyng-Luh Liu (Academia Sinica)

Quaternion Knowledge Graph Embeddings
SHUAI ZHANG (University of New South Wales) · Yi Tay (Nanyang Technological University) · Lina Yao (UNSW) · Qi Liu (Facebook AI Research)

Glyce: Glyph-vectors for Chinese Character Representations
Yuxian Meng (Shannon.AI) · Wei Wu (Shannon.AI) · Fei Wang (Shannon.AI) · Xiaoya Li (Shannon.AI) · Ping Nie (Shannon.AI) · Fan Yin (Shannon.AI) · Muyu Li (Shannon.AI) · Qinghong Han (Shannon.AI) · Xiaofei Sun (Shannon.AI) · Jiwei Li (Shannon.AI)

Turbo Autoencoder: Deep learning based channel code for point-to-point communication channels
Yihan Jiang (University of Washington Seattle) · Hyeji Kim (Samsung AI Center Cambridge) · Himanshu Asnani (University of Washington, Seattle) · Sreeram Kannan (University of Washington) · Sewoong Oh (University of Washington) · Pramod Viswanath (UIUC)

Heterogeneous Graph Learning for Visual Commonsense Reasoning
Weijiang Yu (Sun Yat-sen University) · Jingwen Zhou (Sun Yat-sen University) · Weihao Yu (Sun Yat-sen University) · Xiaodan Liang (Sun Yat-sen University) · Nong Xiao (Sun Yat-sen University)

Probabilistic Watershed: Sampling all spanning forests for seeded segmentation and semi-supervised learning
Enrique Fita Sanmartin (Heidelberg University) · Sebastian Damrich (Heidelberg University) · Fred Hamprecht (Heidelberg University)

Classification-by-Components: Probabilistic Modeling of Reasoning over a Set of Components
Sascha Saralajew (Dr. Ing. h.c. Porsche AG) · Lars Holdijk (Radboud University Nijmegen) · Maike Rees (Dr. Ing. h.c. F. Porsche AG) · Ebubekir Asan (Dr. Ing. h.c. F. Porsche AG) · Thomas Villmann (University of Applied Sciences Mittweida)

Identifying Causal Effects via Context-specific Independence Relations
Santtu Tikka (University of Jyväskylä) · Antti Hyttinen (University of Helsinki) · Juha Karvanen (University of Jyvaskyla)

Bridging Machine Learning and Logical Reasoning by Abductive Learning
Wang-Zhou Dai (Imperial College London) · Qiuling Xu (Purdue University) · Yang Yu (Nanjing University) · Zhi-Hua Zhou (Nanjing University)

Regret Minimization for Reinforcement Learning by Evaluating the Optimal Bias Function
Zihan Zhang (Tsinghua University) · Xiangyang Ji (Tsinghua University)

On the Global Convergence of (Fast) Incremental Expectation Maximization Methods
Belhal Karimi (Ecole Polytechnique) · Hoi-To Wai (Chinese University of Hong Kong) · Eric Moulines (Ecole Polytechnique) · Marc Lavielle (Inria & Ecole Polytechnique)

A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization
Sulaiman Alghunaim (UCLA) · Kun Yuan (UCLA) · Ali H Sayed (Ecole Polytechnique Fédérale de Lausanne)

Regularizing Trajectory Optimization with Denoising Autoencoders
Rinu Boney (Aalto University) · Norman Di Palo (Italian Institute of Technology) · Mathias Berglund (Curious AI) · Alexander Ilin (Aalto University) · Juho Kannala (Aalto University) · Antti Rasmus (The Curious AI Company) · Harri Valpola (Curious AI)

Learning Hierarchical Priors in VAEs
Alexej Klushyn (Volkswagen Group) · Nutan Chen (Volkswagen Group) · Richard Kurle (Volkswagen Group) · Botond Cseke (Volkswagen Group) · Patrick van der Smagt (Volkswagen Group)

Epsilon-Best-Arm Identification in Pay-Per-Reward Multi-Armed Bandits
Sivan Sabato (Ben-Gurion University of the Negev)

Safe Exploration for Interactive Machine Learning
Matteo Turchetta (ETH Zurich) · Felix Berkenkamp (ETH Zurich) · Andreas Krause (ETH Zurich)

Addressing Failure Detection by Learning Model Confidence
Charles Corbière (Valeo.ai / CNAM) · Nicolas THOME (Cnam (Conservatoire national des arts et métiers)) · Avner Bar-Hen (CNAM, Paris) · Matthieu Cord (Sorbonne University) · Patrick Pérez (Valeo.ai)

Combinatorial Bayesian Optimization using the Graph Cartesian Product
Changyong Oh (University of Amsterdam) · Jakub Tomczak (Qualcomm AI Research) · Efstratios Gavves (University of Amsterdam) · Max Welling (University of Amsterdam / Qualcomm AI Research)

Fooling Neural Network Interpretations via Adversarial Model Manipulation
Juyeon Heo (Sungkyunkwan University) · Sunghwan Joo (Sungkyunkwan University) · Taesup Moon (Sungkyunkwan University (SKKU))

On Lazy Training in Differentiable Programming
Lénaïc Chizat (INRIA) · Edouard Oyallon (CentraleSupelec) · Francis Bach (INRIA - Ecole Normale Superieure)

Quality Aware Generative Adversarial Networks
Kancharla Parimala (Indian Institute of Technology, Hyderabad) · Sumohana Channappayya (Indian Institute of Technology Hyderabad)

Copula-like Variational Inference
Marcel Hirt (University College London) · Petros Dellaportas (University College London, Athens University of Economics and Alan Turing Institute) · Alain Durmus (ENS Paris Saclay)

Implicit Regularization for Optimal Sparse Recovery
Tomas Vaskevicius (University of Oxford) · Varun Kanade (University of Oxford) · Patrick Rebeschini (University of Oxford)

Locally Private Gaussian Estimation
Matthew Joseph (University of Pennsylvania) · Janardhan Kulkarni (Microsoft Research) · Jieming Mao (Google Research) · Steven Wu (University of Minnesota)

Multi-mapping Image-to-Image Translation via Learning Disentanglement
Xiaoming Yu (Peking University) · Yuanqi Chen (SECE, Peking University) · Shan Liu (Tencent) · Thomas Li (Shenzhen Graduate School, Peking University) · Ge Li (SECE, Shenzhen Graduate School, Peking University)

Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs
Yusuke Tanaka (NTT) · Toshiyuki Tanaka (Kyoto University) · Tomoharu Iwata (NTT) · Takeshi Kurashima (NTT Corporation) · Maya Okawa (NTT) · Yasunori Akagi (NTT Service Evolution Laboratories, NTT Corporation) · Hiroyuki Toda (NTT Service Evolution Laboratories, NTT Corporation, Japan)

Structured Decoding for Non-Autoregressive Machine Translation
Zhiqing Sun (Carnegie Mellon University) · Zhuohan Li (UC Berkeley) · Haoqing Wang (Peking University) · Di He (Peking University) · Zi Lin (Peking University) · Zhihong Deng (Peking University)

Learning Temporal Pose Estimation from Sparsely-Labeled Videos
Gedas Bertasius (Facebook Research) · Christoph Feichtenhofer (Facebook AI Research) · Du Tran (Facebook AI) · Jianbo Shi (University of Pennsylvania) · Lorenzo Torresani (Facebook AI Research)

Greedy InfoMax for Biologically Plausible Self-Supervised Representation Learning
Sindy Löwe (University of Amsterdam) · Peter O'Connor (University of Amsterdam) · Bastiaan Veeling (AMLab - University of Amsterdam)

Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching
Hongteng Xu (Infinia ML) · Dixin Luo (Duke University) · Lawrence Carin (Duke University)

Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual Recognition
Satoshi Tsutsui (Indiana University) · Yanwei Fu (Fudan University, Shanghai;) · David Crandall (Indiana University)

Real-Time Reinforcement Learning
Simon Ramstedt (Mila) · Chris Pal (Montreal Institute for Learning Algorithms, École Polytechnique, Université de Montréal)

Robust Multi-agent Counterfactual Prediction
Alexander Peysakhovich (Facebook) · Christian Kroer (Columbia University) · Adam Lerer (Facebook AI Research)

Approximate Inference Turns Deep Networks into Gaussian Processes
Mohammad Emtiyaz Khan (RIKEN) · Alexander Immer (EPFL, RIKEN) · Ehsan Abedi (EPFL) · Maciej Korzepa (Technical University of Denmark)

Deep Signatures
Patrick Kidger (University of Oxford) · Patric Bonnier (University of Oxford) · Imanol Perez Arribas (University of Oxford) · Cristopher Salvi (University of Oxford) · Terry Lyons (University of Oxford)

Individual Regret in Cooperative Nonstochastic Multi-Armed Bandits
Yogev Bar-On (Tel-Aviv University) · Yishay Mansour (Tel Aviv University / Google)

Convergent Policy Optimization for Safe Reinforcement Learning
Ming Yu (The University of Chicago, Booth School of Business) · Zhuoran Yang (Princeton University) · Mladen Kolar (University of Chicago) · Zhaoran Wang (Northwestern University)

Augmented Neural ODEs
Emilien Dupont (Oxford University) · Arnaud Doucet (Oxford) · Yee Whye Teh (University of Oxford, DeepMind)

Thompson Sampling for Multinomial Logit Contextual Bandits
Min-hwan Oh (Columbia University) · Garud Iyengar (Columbia)

Backpropagation-Friendly Eigendecomposition
Wei Wang (EPFL) · Zheng Dang (Xi'an Jiaotong University) · Yinlin Hu (EPFL) · Pascal Fua (EPFL, Switzerland) · Mathieu Salzmann (EPFL)

FastSpeech: Fast, Robust and Controllable Text to Speech
Yi Ren (Zhejiang University) · Yangjun Ruan (Zhejiang University) · Xu Tan (Microsoft Research) · Tao Qin (Microsoft Research) · Sheng Zhao (Microsoft) · Zhou Zhao (Zhejiang University) · Tie-Yan Liu (Microsoft Research)

Ultrametric Fitting by Gradient Descent
Giovanni Chierchia (ESIEE Paris) · Benjamin Perret (ESIEE/PARIS)

Distinguishing Distributions When Samples Are Strategically Transformed
Hanrui Zhang (Duke University) · Yu Cheng (Duke University) · Vincent Conitzer (Duke University)

Implicit Regularization of Discrete Gradient Dynamics in Deep Linear Neural Networks
Gauthier Gidel (Mila) · Francis Bach (INRIA - Ecole Normale Superieure) · Simon Lacoste-Julien (Mila, Université de Montréal)

Deep Set Prediction Networks
Yan Zhang (University of Southampton) · Jonathon Hare (University of Southampton) · Adam Prugel-Bennett (apb@ecs.soton.ac.uk)

DppNet: Approximating Determinantal Point Processes with Deep Networks
Zelda Mariet (MIT) · Yaniv Ovadia (Princeton University) · Jasper Snoek (Google Brain)

Efficient Communication in Multi-Agent Reinforcement Learning via Variance Based Control
Sai Qian Zhang (Harvard University) · Qi Zhang (Amazon) · Jieyu Lin (University of Toronto)

Neural Lyapunov Control
Ya-Chien Chang (University of California, San Diego) · Nima Roohi (University of California San Diego) · Sicun Gao (University of California, San Diego)

Fully Dynamic Consistent Facility Location
Vincent Cohen-Addad (CNRS & Sorbonne Université) · Niklas Oskar D Hjuler (University of Copenhagen) · Nikos Parotsidis (University of Copenhagen) · David Saulpic (Ecole normale supérieure) · Chris Schwiegelshohn (Sapienza, University of Rome)

A Stickier Benchmark for General-Purpose Language Understanding Systems
Alex Wang (New York University) · Yada Pruksachatkun (New York University) · Nikita Nangia (NYU) · Amanpreet Singh (Facebook) · Julian Michael (University of Washington) · Felix Hill (Google Deepmind) · Omer Levy (Facebook) · Samuel Bowman (New York University)

A Flexible Generative Framework for Graph-based Semi-supervised Learning
Jiaqi Ma (University of Michigan) · Weijing Tang (University of Michigan) · Ji Zhu (University of Michigan) · Qiaozhu Mei (University of Michigan)

Self-normalization in Stochastic Neural Networks
Georgios Detorakis (University of California, Irvine) · Sourav Dutta (Univ. Notre Dame) · Abhishek Khanna (Univ. Notre Dame) · Matthew Jerry (Univ. Notre Dame) · Suman Datta (Univ. Notre Dame) · Emre Neftci (Institute for Neural Computation, UCSD)

Optimal Decision Tree with Noisy Outcomes
Su Jia (CMU) · viswanath nagarajan (Univ Michigan, Ann Arbor) · Fatemeh Navidi (University of Michigan) · R Ravi (CMU)

Meta-Curvature
Eunbyung Park (UNC Chapel Hill) · Junier Oliva (UNC - Chapel Hill)

Intrinsically Efficient, Stable, and Bounded Off-Policy Evaluation for Reinforcement Learning
Nathan Kallus (Cornell University) · Masatoshi Uehara (Harvard University)

KerGM: Kernelized Graph Matching
Zhen Zhang (WASHINGTON UNIVERSITY IN ST.LOUIS) · Yijian Xiang (Washington University in St. Louis) · Lingfei Wu (IBM Research AI) · Bing Xue (Washington University in St. Louis) · Arye Nehorai (WASHINGTON UNIVERSITY IN ST.LOUIS)

Transfusion: Understanding Transfer Learning for Medical Imaging
Maithra Raghu (Cornell University and Google Brain) · Chiyuan Zhang (Google Brain) · Jon Kleinberg (Cornell University) · Samy Bengio (Google Research, Brain Team)

Adversarial training for free!
Ali Shafahi (University of Maryland) · Mahyar Najibi (University of Maryland) · Mohammad Amin Ghiasi (University of Maryland) · Zheng Xu (Google AI) · John Dickerson (University of Maryland) · Christoph Studer (Cornell University) · Larry Davis (University of Maryland) · Gavin Taylor (US Naval Academy) · Tom Goldstein (University of Maryland)

Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients
Jun Sun (Zhejiang University) · Tianyi Chen (University of Minnesota) · Georgios Giannakis (University of Minnesota) · Zaiyue Yang (Southern University of Science and Technology)

Implicitly learning to reason in first-order logic
Vaishak Belle (University of Edinburgh & Alan Turing Institute) · Brendan Juba (Washington University in St. Louis)

Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods
Kevin Liang (Duke University) · Guoyin Wang (Duke University) · Yitong Li (Duke University) · Ricardo Henao (Duke University) · Lawrence Carin (Duke University)

PC-Fairness: A Unified Framework for Measuring Causality-based Fairness
Yongkai Wu (University of Arkansas) · Lu Zhang (University of Arkansas) · Xintao Wu (University of Arkansas) · Hanghang Tong (Arizona State University)

Arbicon-Net: Arbitrary Continuous Geometric Transformation Networks for Image Registration
Jianchun Chen (New York University) · Lingjing Wang (New York University) · Xiang Li (New York University) · Yi Fang (New York University)

Assessing Disparate Impact of Personalized Interventions: Identifiability and Bounds
Nathan Kallus (Cornell University) · Angela Zhou (Cornell University)

The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the XAUC Metric
Nathan Kallus (Cornell University) · Angela Zhou (Cornell University)

HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models
Sharon Zhou (Stanford University) · Mitchell Gordon (Stanford University) · Ranjay Krishna (Stanford University) · Austin Narcomey (Stanford University) · Li Fei-Fei (Stanford University) · Michael Bernstein (Stanford University)

First order expansion of convex regularized estimators
Pierre Bellec (Rutgers) · Arun Kuchibhotla (Wharton Statistics)

Capacity Bounded Differential Privacy
Kamalika Chaudhuri (UCSD) · Jacob Imola (UCSD) · Ashwin Machanavajjhala (Duke)

Universal Boosting Variational Inference
Trevor Campbell (UBC) · Xinglong Li (The University of British Columbia)

SGD on Neural Networks Learns Functions of Increasing Complexity
Dimitris Kalimeris (Harvard) · Gal Kaplun (Harvard University) · Preetum Nakkiran (Harvard) · Benjamin Edelman (Harvard University) · Tristan Yang (Harvard University) · Boaz Barak (Harvard University) · Haofeng Zhang (Harvard University)

The Landscape of Non-convex Empirical Risk with Degenerate Population Risk
Shuang Li (Colorado School of Mines) · Gongguo Tang (Colorado School of Mines) · Michael B Wakin (Colorado School of Mines)

Making AI Forget You: Data Deletion in Machine Learning
Antonio Ginart (Stanford University) · Melody Guan (Stanford University) · Gregory Valiant (Stanford University) · James Zou (Stanford)

Practical Differentially Private Top-k Selection with Pay-what-you-get Composition
David Durfee (Georgia Tech) · Ryan Rogers (LinkedIn)

Conformalized Quantile Regression
Yaniv Romano (Stanford University) · Evan Patterson (Stanford University) · Emmanuel Candes (Stanford University)

Thompson Sampling with Information Relaxation Penalties
Seungki Min (Columbia Business School) · Costis Maglaras (Columbia Business School) · Ciamac C Moallemi (Columbia University)

Deep Generalized Method of Moments for Instrumental Variable Analysis
Andrew Bennett (Cornell University) · Nathan Kallus (Cornell University) · Tobias Schnabel (Microsoft Research)

Learning Sample-Specific Models with Low-Rank Personalized Regression
Ben Lengerich (Carnegie Mellon University) · Bryon Aragam (University of Chicago) · Eric Xing (Petuum Inc. / Carnegie Mellon University)

Dance to Music
Hsin-Ying Lee (University of California, Merced) · Xiaodong Yang (NVIDIA Research) · Ming-Yu Liu (Nvidia Research) · Ting-Chun Wang (NVIDIA) · Yu-Ding Lu (UC Merced) · Ming-Hsuan Yang (Google / UC Merced) · Jan Kautz (NVIDIA)

Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask
Hattie Zhou (Uber) · Janice Lan (Uber AI Labs) · Rosanne Liu (Uber AI Labs) · Jason Yosinski (Uber AI Labs)

Implicit Generation and Modeling with Energy Based Models
Yilun Du (MIT) · Igor Mordatch (OpenAI)

Who Learns? Decomposing Learning into Per-Parameter Loss Contribution
Janice Lan (Uber AI Labs) · Rosanne Liu (Uber AI Labs) · Hattie Zhou (Uber) · Jason Yosinski (Uber AI Labs)

Predicting the Politics of an Image Using Webly Supervised Data
Christopher Thomas (University of Pittsburgh) · Adriana Kovashka (University of Pittsburgh)

Adaptive GNN for Image Analysis and Editing
Lingyu Liang (South China University of Technology) · LianWen Jin (South China University of Technology) · Yong Xu (South China University of Technology)

Ultra Fast Medoid Identification via Correlated Sequential Halving
Tavor Baharav (Stanford University) · David Tse (Stanford University)

Tight Dimension Independent Lower Bound on the Expected Convergence Rate for Diminishing Step Sizes in SGD
PHUONG_HA NGUYEN (University of Connecticut (UCONN)) · Lam Nguyen (IBM Thomas J. Watson Research Center) · Marten van Dijk (University of Connecticut)

Asymptotics for Sketching in Least Squares Regression
Edgar Dobriban (University of Pennsylvania) · Sifan Liu (Stanford University)

MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies
Xue Bin Peng (UC Berkeley) · Michael Chang (University of California, Berkeley) · Grace Zhang (UC Berkeley) · Pieter Abbeel (UC Berkeley & covariant.ai) · Sergey Levine (UC Berkeley)

Exact inference in structured prediction
Kevin Bello (Purdue University) · Jean Honorio (Purdue University)

Coda: An End-to-End Neural Program Decompiler
Cheng Fu (University of California, San Diego) · Huili Chen (UCSD) · Haolan Liu (UCSD) · Xinyun Chen (UC Berkeley) · Yuandong Tian (Facebook AI Research) · Farinaz Koushanfar (UCSD) · Jishen Zhao (UCSD)

Bat-G net: Bat-inspired High-Resolution 3D Image Reconstruction using Ultrasonic Echoes
Gunpil Hwang (KAIST) · Seohyeon Kim (KAIST) · Hyeon-Min Bae (KAIST)

Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates
Sharan Vaswani (Mila, Université de Montréal) · Aaron Mishkin (University of British Columbia) · Issam Laradji (University of British Columbia) · Mark Schmidt (University of British Columbia) · Gauthier Gidel (Mila) · Simon Lacoste-Julien (Mila, Université de Montréal)

Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data
Dominik Linzner (Technische Universität Darmstadt) · Michael Schmidt (TU Darmstadt) · Heinz Koeppl (Technische Universität Darmstadt)

Privacy-Preserving Classification of Personal Text Messages with Secure Multi-Party Computation
Devin Reich (University of Washington Tacoma) · Ariel Todoki (University of Washington Tacoma) · Rafael Dowsley (Bar-Ilan University) · Martine De Cock (University of Washington Tacoma) · anderson nascimento (UW)

Efficiently Estimating Erdos-Renyi Graphs with Node Differential Privacy
Jonathan Ullman (Northeastern University) · Adam Sealfon (UC Berkeley)

Learning Representations for Time Series Clustering
Qianli Ma (South China University of Technology) · Jiawei Zheng (South China University of Technology) · Sen Li (South China University of Technology) · Gary W Cottrell (UCSD)

Variance Reduced Uncertainty Calibration
Ananya Kumar (Stanford University) · Percy Liang (Stanford University) · Tengyu Ma (Stanford)

A Normative Theory for Causal Inference and Bayes Factor Computation in Neural Circuits
Wenhao Zhang (Carnegie Mellon & U. of Pittsburgh) · Si Wu (Peking University) · Brent Doiron (University of Pittsburgh) · Tai Sing Lee (Carnegie Mellon University)

Unsupervised Keypoint Learning for Guiding Class-conditional Video Prediction
Yunji Kim (Yonsei University) · Seonghyeon Nam (Yonsei University) · In Cho (Yonsei University) · Seon Joo Kim (Yonsei University / Facebook)

Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks
Yiwen Guo (Intel Labs China) · Ziang Yan (Tsinghua University) · Changshui Zhang (Tsinghua University)

Stochastic Gradient Hamiltonian Monte Carlo Methods with Recursive Variance Reduction
Difan Zou (University of California, Los Angeles) · Pan Xu (University of California, Los Angeles) · Quanquan Gu (UCLA)

Learning Latent Process from High-Dimensional Event Sequences via Efficient Sampling
Qitian Wu (Shanghai Jiao Tong University) · Zixuan Zhang (Shanghai Jiao Tong University) · Xiaofeng Gao (Shanghai Jiao Tong University) · Junchi Yan (Shanghai Jiao Tong University) · Guihai Chen (Shanghai Jiao Tong University)

Cross-sectional Learning of Extremal Dependence among Financial Assets
Xing Yan (City University of Hong Kong) · Qi Wu (City University of Hong Kong) · Wen Zhang (JD Finance)

Principal Component Projection and Regression in Nearly Linear Time through Asymmetric SVRG
Yujia Jin (Stanford University) · Aaron Sidford (Stanford)

Compression with Flows via Local Bits-Back Coding
Jonathan Ho (UC Berkeley) · Evan Lohn (University of California, Berkeley) · Pieter Abbeel (UC Berkeley & covariant.ai)

Exact Rate-Distortion in Autoencoders via Echo Noise
Rob Brekelmans (University of Southern Caifornia) · Daniel Moyer (University of Southern California) · Aram Galstyan (USC Information Sciences Inst) · Greg Ver Steeg (University of Southern California)

iSplit LBI: Individualized Partial Ranking with Ties via Split LBI
Qianqian Xu (Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences) · Xinwei Sun (MSRA) · Zhiyong Yang (SKLOIS, Institute of Information Engineering, Chinese Academy of Sciences; SCS, University of Chinese Academy of Sciences) · Xiaochun Cao (Institute of Information Engineering, Chinese Academy of Sciences) · Qingming Huang (University of Chinese Academy of Sciences) · Yuan Yao (Hong Kong Univ. of Science & Technology)

Self-Supervised Active Triangulation for 3D Human Pose Reconstruction
Aleksis Pirinen (Lund University) · Erik Gärtner (Lund University) · Cristian Sminchisescu (LTH)

MetaQuant: Learning to Quantize by Learning to Penetrate Non-differentiable Quantization
Shangyu Chen (Nanyang Technological University, Singapore) · Wenya Wang (Nanyang Technological University) · Sinno Jialin Pan (Nanyang Technological University, Singapore)

Improved Precision and Recall Metric for Assessing Generative Models
Tuomas Kynkäänniemi (NVIDIA; Aalto University) · Tero Karras (NVIDIA) · Samuli Laine (NVIDIA) · Jaakko Lehtinen (Aalto University & NVIDIA) · Timo Aila (NVIDIA)

A First-order Algorithmic Framework for Distributionally Robust Logistic Regression
JIAJIN LI (The Chinese University of Hong Kong) · SEN HUANG (The Chinese University of Hong Kong) · Anthony Man-Cho So (CUHK)

PasteGAN: A Semi-Parametric Method to Generate Image from Scene Graph
Yikang LI (The Chinese University of Hong Kong; Sensetime) · Tao Ma (Northwestern Polytechnical University) · Yeqi Bai (Nanyang Technological University) · Nan Duan (Microsoft Research Asia) · Sining Wei (Microsoft Research) · Xiaogang Wang (The Chinese University of Hong Kong)

Concomitant Lasso with Repetitions (CLaR): beyond averaging multiple realizations of heteroscedastic noise
Quentin Bertrand (INRIA) · Mathurin Massias (Inria) · Alexandre Gramfort (INRIA) · Joseph Salmon (Université de Montpellier)

Joint Optimization of Tree-based Index and Deep Model for Recommender Systems
Han Zhu (Alibaba Group) · Daqing Chang (Alibaba Group) · Ziru Xu (Alibaba Group) · Pengye Zhang (Alibaba Group) · Xiang Li (Alibaba Group) · Jie He (Alibaba Group) · Han Li (Alibaba Group) · Jian Xu (Alibaba Group) · Kun Gai (Alibaba Group)

Learning Generalizable Device Placement Algorithms for Distributed Machine Learning
ravichandra addanki (Massachusetts Institute of Technology) · Shaileshh Bojja Venkatakrishnan (Massachusetts Institute of Technology) · Shreyan Gupta (MIT) · Hongzi Mao (MIT) · Mohammad Alizadeh (Massachusetts Institute of Technology)

Uncoupled Regression from Pairwise Comparison Data
Ritsugen Jo (UCL) · Junya Honda (The Univerisity of Tokyo / RIKEN) · Gang Niu (RIKEN) · Masashi Sugiyama (RIKEN / University of Tokyo)

Cross Attention Network for Few-shot Classification
Ruibing Hou (Institute of Computing Technology，Chinese Academy) · Hong Chang (Institute of Computing Technology, Chinese Academy of Sciences) · Bingpeng MA (University of Chinese Academy of Sciences) · Shiguang Shan (Chinese Academy of Sciences) · Xilin Chen (Institute of Computing Technology, Chinese Academy of Sciences)

A Nonconvex Approach for Exact and Efficient Multichannel Sparse Blind Deconvolution
Qing Qu (New York University) · Xiao Li (The Chinese University of Hong Kong) · Zhihui Zhu (Johns Hopkins University)

SCAN: A Scalable Neural Networks Framework Towards Compact and Efficient Models
Linfeng Zhang (Tsinghua University ) · Zhanhong Tan (Tsinghua University) · Jiebo Song (Institute for Interdisciplinary Information Core Technology) · Jingwei Chen (Tsinghua University) · Chenglong Bao (Tsinghua university) · Kaisheng Ma (Tsinghua University)

Revisiting the Bethe-Hessian: Improved Community Detection in Sparse Heterogeneous Graphs
Lorenzo Dall'Amico (GIPSA lab) · Romain Couillet (CentralSupélec) · Nicolas Tremblay (CNRS)

Teaching Multiple Concepts to a Forgetful Learner
Anette Hunziker (ETH Zurich) · Yuxin Chen (Caltech) · Oisin Mac Aodha (California Institute of Technology) · Manuel Gomez Rodriguez (Max Planck Institute for Software Systems) · Andreas Krause (ETH Zurich) · Pietro Perona (California Institute of Technology) · Yisong Yue (Caltech) · Adish Singla (MPI-SWS)

Regularized Weighted Low Rank Approximation
Frank Ban (UC Berkeley) · David Woodruff (Carnegie Mellon University) · Richard Zhang (UC Berkeley)

Practical and Consistent Estimation of f-Divergences
Paul Rubenstein (MPI for IS) · Olivier Bousquet (Google Brain (Zurich)) · Josip Djolonga (Google Research, Brain Team) · Carlos Riquelme (Google Brain) · Ilya Tolstikhin (MPI for Intelligent Systems)

Approximation Ratios of Graph Neural Networks for Combinatorial Problems
Ryoma Sato (Kyoto University) · Makoto Yamada (Kyoto University/RIKEN AIP) · Hisashi Kashima (Kyoto University/RIKEN Center for AIP)

Thinning for Accelerating the Learning of Point Processes
Tianbo Li (Nanyang Technological University) · Yiping Ke (Nanyang Technological University)

A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models
Maxim Kuznetsov (Insilico Medicine) · Daniil Polykovskiy (Insilico Medicine) · Dmitry Vetrov (Higher School of Economics, Samsung AI Center, Moscow) · Alexander Zhebrak (Insilico Medicine)

Differentially Private Markov Chain Monte Carlo
Mikko Heikkilä (University of Helsinki) · Joonas Jälkö (Aalto University) · Onur Dikmen (Halmstad University) · Antti Honkela (University of Helsinki)

Full-Gradient Representation for Neural Network Visualization
Suraj Srinivas (Idiap Research Institute & EPFL) · François Fleuret (Idiap Research Institute)

q-means: A quantum algorithm for unsupervised machine learning
Iordanis Kerenidis (Université Paris Diderot) · Jonas Landman (Université Paris Diderot) · Alessandro Luongo (IRIF - Atos quantum lab) · Anupam Prakash (Université Paris Diderot)

Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints
Sebastian Tschiatschek (Microsoft Research) · Ahana Ghosh (MPI-SWS) · Luis Haug (ETH Zurich) · Rati Devidze (MPI-SWS) · Adish Singla (MPI-SWS)

Limitations of the empirical Fisher approximation
Frederik Kunstner (EPFL) · Philipp Hennig (University of Tübingen and MPI for Intelligent Systems Tübingen) · Lukas Balles (University of Tuebingen)

Flow-based Image-to-Image Translation with Feature Disentanglement
Ruho Kondo (Toyota Central R&D Labs., Inc.) · Keisuke Kawano (Toyota Central R&D Labs., Inc) · Satoshi Koide (Toyota Central R&D Labs.) · Takuro Kutsuna (Toyota Central R&D Labs. Inc.)

Learning dynamic semi-algebraic proofs
Alhussein Fawzi (DeepMind) · Mateusz Malinowski (DeepMind) · Hamza Fawzi (University of Cambridge) · Omar Fawzi (ENS Lyon)

Shape and Time Distorsion Loss for Training Deep Time Series Forecasting Models
Vincent LE GUEN (CNAM, Paris, France) · Nicolas THOME (Cnam (Conservatoire national des arts et métiers))

Understanding attention in graph neural networks
Boris Knyazev (University of Guelph) · Graham W Taylor (University of Guelph) · Mohamed R. Amer (Robust.AI)

Data Cleansing for Models Trained with SGD
Satoshi Hara (Osaka University) · Atsushi Nitanda (The University of Tokyo / RIKEN) · Takanori Maehara (RIKEN AIP)

Curvilinear Distance Metric Learning
Shuo Chen (Nanjing University of Science and Technology) · Lei Luo (Pitt) · Jian Yang (Nanjing University of Science and Technology) · Chen Gong (Nanjing University of Science and Technology) · Jun Li (MIT) · Heng Huang (University of Pittsburgh)

Semantically-Regularized Logic Graph Embeddings
Xie Yaqi (National University of Singapore) · Ziwei Xu (National University of Singapore) · Kuldeep S Meel (National University of Singapore) · Mohan Kankanhalli (National University of Singapore,) · Harold Soh (National University of Singapore (NUS))

Modeling Uncertainty by Learning A Hierarchy of Deep Neural Connections
Raanan Yehezkel Rohekar (Intel AI Lab) · Yaniv Gurwicz (Intel AI Lab) · Shami Nisimov (Intel AI Lab) · Gal Novik (Intel AI Lab)

Efficient Graph Generation with Graph Recurrent Attention Networks
Renjie Liao (University of Toronto) · Yujia Li (DeepMind) · Yang Song (Stanford University) · Shenlong Wang (University of Toronto) · Will Hamilton (McGill) · David Duvenaud (University of Toronto) · Raquel Urtasun (Uber ATG) · Richard Zemel (Vector Institute/University of Toronto)

Beyond Alternating Updates for Matrix Factorization with Inertial Bregman Proximal Gradient Algorithms
Mahesh Chandra Mukkamala (Saarland University) · Peter Ochs (Saarland University)

Learning Deep Bilinear Transformation for Fine-grained Image Representation
Heliang Zheng (University of Science and Technology of China) · Jianlong Fu (Microsoft Research) · Zheng-Jun Zha (University of Science and Technology of China) · Jiebo Luo (U. Rochester)

Practical Deep Learning with Bayesian Principles
Kazuki Osawa (Tokyo Institute of Technology) · Siddharth Swaroop (University of Cambridge) · Mohammad Emtiyaz Khan (RIKEN) · Anirudh Jain (Indian Institute of Technology (ISM), Dhanbad) · Runa Eschenhagen (University of Osnabrueck) · Richard E Turner (University of Cambridge) · Rio Yokota (Tokyo Institute of Technology, AIST- Tokyo Tech Real World Big-Data Computation Open Innovation Laboratory (RWBC- OIL), National Institute of Advanced Industrial Science and Technology (AIST))

Training Language GANs from Scratch
Cyprien de Masson d'Autume (Google DeepMind) · Shakir Mohamed (DeepMind) · Mihaela Rosca (Google DeepMind) · Jack Rae (DeepMind, UCL)

Pseudo-Extended Markov chain Monte Carlo
Christopher Nemeth (Lancaster University) · Fredrik Lindsten (Linköping University) · Maurizio Filippone (EURECOM) · James Hensman (PROWLER.io)

Differentially Private Bagging: Improved utility and cheaper privacy than subsample-and-aggregate
James Jordon (University of Oxford) · Jinsung Yoon (University of California, Los Angeles) · Mihaela van der Schaar (University of Cambridge, Alan Turing Institute and UCLA)

Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters
Alberto Maria Metelli (Politecnico di Milano) · Amarildo Likmeta (Politecnico di Milano) · Marcello Restelli (Politecnico di Milano)

On Adversarial Mixup Resynthesis
Christopher Beckham (Mila) · Sina Honari (Mila & University of Montreal) · Alex Lamb (UMontreal (MILA)) · Vikas Verma (Aalto University) · Farnoosh Ghadiri (École Polytechnique de Montréal) · R Devon Hjelm (Microsoft Research) · Yoshua Bengio (Mila) · Chris Pal (MILA, Polytechnique Montréal, Element AI)

A Geometric Perspective on Optimal Representations for Reinforcement Learning
Marc Bellemare (Google Brain) · Will Dabney (DeepMind) · Robert Dadashi (Google Brain) · Adrien Ali Taiga (Google) · Pablo Samuel Castro (Google) · Nicolas Le Roux (Google Brain) · Dale Schuurmans (Google Inc.) · Tor Lattimore (DeepMind) · Clare Lyle (University of Oxford)

Learning New Tricks From Old Dogs: Multi-Source Transfer Learning From Pre-Trained Networks
Joshua Lee (MIT) · Prasanna Sattigeri (IBM Research) · Gregory Wornell (MIT)

Understanding and Improving Layer Normalization
Jingjing Xu (Peking University) · Xu Sun (Peking University) · Zhiyuan Zhang (Peking University) · Guangxiang Zhao (Peking University) · Junyang Lin (Alibaba Group)

Uncertainty-based Continual Learning with Adaptive Regularization
Hongjoon Ahn (Sunkyunkwan University) · Donggyu Lee (Sungkyunkwan university) · Sungmin Cha (Sungkyunkwan University) · Taesup Moon (Sungkyunkwan University (SKKU))

LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning
Yali Du (University of Technology Sydney) · Lei Han (Rutgers University) · Meng Fang (Tencent) · Ji Liu (University of Rochester, Tencent AI lab) · Tianhong Dai (Imperial College London) · Dacheng Tao (University of Sydney)

U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging
Mathias Perslev (University of Copenhagen) · Michael Jensen (University of Copehagen) · Sune Darkner (University of Copenhagen, Denmark) · Poul Jørgen Jennum (Danish Center for Sleep Medicine, Rigshospitalet) · Christian Igel (University of Copenhagen)

Massively scalable Sinkhorn distances via the Nyström method
Jason Altschuler (MIT) · Francis Bach (INRIA - Ecole Normale Superieure) · Alessandro Rudi (INRIA, Ecole Normale Superieure) · Jonathan Niles-Weed (NYU)

Double Quantization for Communication-Efficient Distributed Optimization
Yue Yu (Tsinghua University) · Jiaxiang Wu (Tencent AI Lab) · Longbo Huang (IIIS, Tsinghua Univeristy)

Globally optimal score-based learning of directed acyclic graphs in high-dimensions
Bryon Aragam (University of Chicago) · Arash Amini (UCLA) · Qing Zhou (UCLA)

Multi-relational Poincaré Graph Embeddings
Ivana Balazevic (University of Edinburgh) · Carl Allen (University of Edinburgh) · Timothy Hospedales (University of Edinburgh)

No-Press Diplomacy: Modeling Multi-Agent Gameplay
Philip Paquette (Université de Montréal - MILA) · Yuchen Lu (University of Montreal) · SETON STEVEN BOCCO (MILA) · Max Smith (University of Michigan) · Satya O.-G. (MILA) · Jonathan K. Kummerfeld (University of Michigan) · Joelle Pineau (McGill University) · Satinder Singh (University of Michigan) · Aaron Courville (U. Montreal)

State Aggregation Learning from Markov Transition Data
Yaqi Duan (Princeton University) · Tracy Ke (Harvard University) · Mengdi Wang (Princeton University)

Disentangling Influence: Using disentangled representations to audit model predictions
Charles Marx (Haverford College) · Richard Phillips (Cornell University) · Sorelle Friedler (Haverford College) · Carlos Scheidegger (The University of Arizona) · Suresh Venkatasubramanian (University of Utah)

Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning
David Janz (University of Cambridge) · Jiri Hron (University of Cambridge) · Przemysław Mazur (Wayve) · Katja Hofmann (Microsoft Research) · José Miguel Hernández-Lobato (University of Cambridge) · Sebastian Tschiatschek (Microsoft Research)

Partially Encrypted Deep Learning using Functional Encryption
Theo Ryffel (École Normale Supérieure) · David Pointcheval (École Normale Supérieure) · Francis Bach (INRIA - Ecole Normale Superieure) · Edouard Dufour-Sans (Carnegie Mellon University) · Romain Gay (UC Berkeley)

Decentralized Cooperative Stochastic Bandits
David Martínez-Rubio (University of Oxford) · Varun Kanade (University of Oxford) · Patrick Rebeschini (University of Oxford)

Statistical bounds for entropic optimal transport: sample complexity and the central limit theorem
Gonzalo Mena (Harvard) · Jonathan Niles-Weed (NYU)

Efficient Deep Approximation of GMMs
Shirin Jalali (Nokia Bell Labs) · Carl Nuzman (Nokia Bell Labs) · Iraj Saniee (Nokia Bell Labs)

Learning low-dimensional state embeddings and metastable clusters from time series data
Yifan Sun (Carnegie Mellon University) · Yaqi Duan (Princeton University) · Hao Gong (Princeton University) · Mengdi Wang (Princeton University)

Exploiting Local and Global Structure for Point Cloud Semantic Segmentation with Contextual Point Representations
Xu Wang (Shenzhen University) · Jingming He (Shenzhen University) · Lin Ma (Tencent AI Lab)

Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes
Creighton Heaukulani (No Affiliation) · Mark van der Wilk (PROWLER.io)

Kernel Instrumental Variable Regression
Rahul Singh (MIT) · Maneesh Sahani (Gatsby Unit, UCL) · Arthur Gretton (Gatsby Unit, UCL)

Symmetry-Based Disentangled Representation Learning requires Interaction with Environments
Hugo Caselles-Dupré (Flowers Laboratory (ENSTA ParisTech & INRIA) & Softbank Robotics Europe) · Michael Garcia Ortiz (SoftBank Robotics Europe) · David Filliat (ENSTA)

Fast Efficient Hyperparameter Tuning for Policy Gradient Methods
Supratik Paul (University of Oxford) · Vitaly Kurin (RWTH Aachen University) · Shimon Whiteson (University of Oxford)

Offline Contextual Bayesian Optimization
Ian Char (Carnegie Mellon University) · Youngseog Chung (Carnegie Mellon University) · Willie Neiswanger (Carnegie Mellon University) · Kirthevasan Kandasamy (Carnegie Mellon University) · Oak Nelson (Princeton Plasma Physics Lab) · Mark Boyer (Princeton Plasma Physics Lab) · Egemen Kolemen (Princeton Plasma Physics Lab) · Jeff Schneider (Carnegie Mellon University)

Making the Cut: A Bandit-based Approach to Tiered Interviewing
Candice Schumann (University of Maryland) · Zhi Lang (University of Maryland, College Park) · Jeffrey Foster (Tufts University) · John Dickerson (University of Maryland)

Unsupervised Scalable Representation Learning for Multivariate Time Series
Jean-Yves Franceschi (Sorbonne Université) · Aymeric Dieuleveut (Ecole Polytechnique, IPP Paris) · Martin Jaggi (EPFL)

A state-space model for inferring effective connectivity of latent neural dynamics from simultaneous EEG/fMRI
Tao Tu (Columbia University) · John Paisley (Columbia University) · Stefan Haufe (Charité – Universitätsmedizin Berlin) · Paul Sajda (Columbia University)

End to end learning and optimization on graphs
Bryan Wilder (Harvard University) · Eric Ewing (University of Southern California) · Bistra Dilkina (University of Southern California) · Milind Tambe (USC)

Game Design for Eliciting Distinguishable Behavior
Fan Yang (Carnegie Mellon University) · Liu Leqi (Carnegie Mellon University) · Yifan Wu (Carnegie Mellon University) · Zachary Lipton (Carnegie Mellon University) · Pradeep Ravikumar (Carnegie Mellon University) · Tom M Mitchell (Carnegie Mellon University) · William Cohen (Google AI)

When does label smoothing help?
Rafael Müller (Google Brain) · Simon Kornblith (Google Brain) · Geoffrey E Hinton (Google & University of Toronto)

Finite-Time Performance Bounds and Adaptive Learning Rate Selection for Two Time-Scale Reinforcement Learning
Harsh Gupta (University of Illinois at Urbana-Champaign) · R. Srikant (University of Illinois at Urbana-Champaign) · Lei Ying (ASU)

Rethinking Deep Neural Network Ownership Verification: Embedding Passports to Defeat Ambiguity Attacks
Lixin Fan (WeBank AI Lab) · Kam Woh Ng (University of Malaya) · Chee Seng Chan (University of Malaya)

Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference
Cole Hurwitz (University of Edinburgh) · Kai Xu (University of Ediburgh) · Akash Srivastava (MIT–IBM Watson AI Lab) · Alessio Buccino (University of Oslo) · Matthias Hennig (University of Edinburgh)

Optimal Sketching for Kronecker Product Regression and Low Rank Approximation
Huaian Diao (Northeast Normal University) · Rajesh Jayaram (Carnegie Mellon University) · Zhao Song (UT-Austin) · Wen Sun (Microsoft Research) · David Woodruff (Carnegie Mellon University)

Distribution-Independent PAC Learning of Halfspaces with Massart Noise
Ilias Diakonikolas (USC) · Themis Gouleakis (MPI) · Christos Tzamos (Microsoft Research)

The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies
Basri Ronen (Weizmann Inst.) · David Jacobs (University of Maryland, USA) · Yoni Kasten (Weizmann Institute) · Shira Kritchman (Weizmann Institute)

Online Learning for Auxiliary Task Weighting for Reinforcement Learning
Xingyu Lin (Carnegie Mellon University) · Harjatin Baweja (CMU) · George Kantor (CMU) · David Held (CMU)

Blocking Bandits
Soumya Basu (University of Texas at Austin) · Rajat Sen (Amazon) · Sujay Sanghavi (UT-Austin) · Sanjay Shakkottai (University of Texas at Austin)

Global Convergence of Least Squares EM for Demixing Two Log-Concave Densities
Wei Qian (Cornell Univeristy) · Yuqian Zhang (Cornell University) · Yudong Chen (Cornell University)

Prior-Free Dynamic Auctions with Low Regret Buyers
Yuan Deng (Duke University) · Jon Schneider (Google Research) · Balasubramanian Sivan (Google Research)

On Single Source Robustness in Deep Fusion Models
Taewan Kim (Amazon) · Joydeep Ghosh (UT Austin)

Policy Evaluation with Latent Confounders via Optimal Balance
Andrew Bennett (Cornell University) · Nathan Kallus (Cornell University)

Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting
Rajat Sen (Amazon) · Hsiang-Fu Yu (Amazon) · Inderjit S Dhillon (UT Austin & Amazon)

Adaptive Cross-Modal Few-shot Learning
Chen Xing (Montreal Institute of Learning Algorithms) · Negar Rostamzadeh (Elemenet AI) · Boris Oreshkin (Element AI) · Pedro O. Pinheiro (Element AI)

Spectral Modification of Graphs for Improved Spectral Clustering
Ioannis Koutis (New Jersey Institute of Technology) · Huong Le (NJIT)

Hyperbolic Graph Convolutional Neural Networks
Zhitao Ying (Stanford University) · Ines Chami (Stanford University) · Christopher Ré (Stanford) · Jure Leskovec (Stanford University and Pinterest)

Cost Effective Active Search
Shali Jiang (Washington University in St. Louis) · Roman Garnett (Washington University in St. Louis) · Benjamin Moseley (Carnegie Mellon University)

Exploration Bonus for Regret Minimization in Discrete and Continuous Average Reward MDPs
Jian QIAN (INRIA Lille - Sequel Team) · Ronan Fruit (Inria Lille) · Matteo Pirotta (Facebook AI Research) · Alessandro Lazaric (Facebook Artificial Intelligence Research)

Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks
Xiao Sun (IBM Thomas J. Watson Research Center) · Jungwook Choi (Hanyang University) · Chia-Yu Chen (IBM research) · Naigang Wang (IBM T. J. Watson Research Center) · Swagath Venkataramani (IBM Research) · Vijayalakshmi (Viji) Srinivasan (IBM TJ Watson) · Xiaodong Cui (IBM T. J. Watson Research Center) · Wei Zhang (IBM T.J.Watson Research Center) · Kailash Gopalakrishnan (IBM Research)

A Stratified Approach to Robustness for Randomly Smoothed Classifiers
Guang-He Lee (MIT) · Yang Yuan (MIT) · Shiyu Chang (IBM T.J. Watson Research Center) · Tommi Jaakkola (MIT)

Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees
Ruqi Zhang (Cornell University) · Christopher De Sa (Cornell)

One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers
Ari Morcos (Facebook AI Research) · Haonan Yu (Facebook AI Research) · Michela Paganini (Facebook) · Yuandong Tian (Facebook AI Research)

Breaking the Glass Ceiling for Embedding-Based Classifiers for Large Output Spaces
Chuan Guo (Cornell University) · Ali Mousavi (Google Brain) · Xiang Wu (ByteDance) · Daniel Holtmann-Rice (Google Inc) · Satyen Kale (Google) · Sashank Reddi (Google) · Sanjiv Kumar (Google Research)

Fair Algorithms for Clustering
Maryam Negahbani (Dartmouth College) · Deeparnab Chakrabarty (Dartmouth) · Nicolas Flores (Dartmouth College) · Suman Bera (University of California Santa Cruz)

Learning Mean-Field Games
Xin Guo (University of California, Berkeley) · Anran Hu (University of Californian, Berkeley (UC Berkeley)) · Renyuan Xu (University of Oxford) · Junzi Zhang (Stanford University)

SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained Microcontrollers
Igor Fedorov (Arm Research) · Ryan Adams (Princeton University) · Matthew Mattina (ARM) · Paul Whatmough (Arm Research)

Deep imitation learning for molecular inverse problems
Eric Jonas (University of Chicago)

Visual Concept-Metaconcept Learning
Chi Han (Tsinghua University) · Jiayuan Mao (MIT) · Chuang Gan (MIT-IBM Watson AI Lab) · Josh Tenenbaum (MIT) · Jiajun Wu (MIT)

Adaptive Video-to-Video Synthesis via Network Weight Generation
Ting-Chun Wang (NVIDIA) · Ming-Yu Liu (Nvidia Research) · Andrew Tao (Nvidia Corporation) · Fitsum Reda (NVIDIA) · Bryan Catanzaro (NVIDIA) · Jan Kautz (NVIDIA)

Neural Similarity Learning
Weiyang Liu (Georgia Institute of Technology) · Zhen Liu (MILA, University of Montreal) · James M Rehg (Georgia Tech) · Le Song (Georgia Institute of Technology)

Ordered Memory
Yikang Shen (Mila, University of Montreal, MSR Montreal) · Shawn Tan (Mila) · Arian Hosseini (Mila, University of Montreal, MSR Montreal) · Zhouhan Lin (MILA) · Alessandro Sordoni (Microsoft Research) · Aaron Courville (U. Montreal)

MixMatch: A Holistic Approach to Semi-Supervised Learning
David Berthelot (Google Brain) · Nicholas Carlini (Google) · Ian Goodfellow (Google Brain) · Nicolas Papernot (University of Toronto) · Avital Oliver (Google Brain) · Colin A Raffel (Google Brain)

Deep Multivariate Quantiles for Novelty Detection
Jingjing Wang (University of Waterloo) · Sun Sun (National Research Council) · Yaoliang Yu (University of Waterloo)

Fast Parallel Algorithms for Statistical Subset Selection Problems
Sharon Qian (Harvard) · Yaron Singer (Harvard University)

PHYRE: A New Benchmark for Physical Reasoning
Anton Bakhtin (Facebook AI Research) · Laurens van der Maaten (Facebook) · Justin Johnson (University of Michigan / FAIR) · Laura Gustafson (Facebook AI Research) · Ross Girshick (FAIR)

How many variables should be entered in a principal component regression equation?
Ji Xu (Columbia University) · Daniel Hsu (Columbia University)

Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery
Jicong Fan (Cornell University) · Lijun Ding (Cornell University) · Yudong Chen (Cornell University) · Madeleine Udell (Cornell University)

Mutually Regressive Point Processes
Ifigeneia Apostolopoulou (Carnegie Mellon University) · Scott Linderman (Stanford University) · Kyle Miller (Carnegie Mellon University) · Artur Dubrawski (Carnegie Mellon University)

Data-driven Estimation of Sinusoid Frequencies
Gautier Izacard (Ecole Polytechnique) · Sreyas Mohan (NYU) · Carlos Fernandez-Granda (NYU)

E2-Train: Energy-Efficient Deep Network Training with Data-, Model-, and Algorithm-Level Saving
Ziyu Jiang (Texas A&M University) · Yue Wang (Rice University) · Xiaohan Chen (Texas A&M University) · Pengfei Xu (Rice University) · Yang Zhao (Rice University) · Yingyan Lin (Rice University) · Zhangyang Wang (TAMU)

ANODEV2: A Coupled Neural ODE Framework
Tianjun Zhang (University of California, Berkeley) · Zhewei Yao (UC Berkeley) · Amir Gholami (University of California, Berkeley) · Joseph Gonzalez (UC Berkeley) · Kurt Keutzer (EECS, UC Berkeley) · Michael W Mahoney (UC Berkeley) · George Biros (University of Texas at Austin)

Estimating Entropy of Distributions in Constant Space
Jayadev Acharya (Cornell University) · Sourbh Bhadane (Cornell University) · Piotr Indyk (MIT) · Ziteng Sun (Cornell University)

On the Utility of Learning about Humans for Human-AI Coordination
Micah Carroll (UC Berkeley) · Rohin Shah (UC Berkeley) · Mark Ho (Princeton University) · Tom Griffiths (Princeton University) · Sanjit Seshia (UC Berkeley) · Pieter Abbeel (UC Berkeley & covariant.ai) · Anca Dragan (UC Berkeley)

Efficient Regret Minimization Algorithm for Extensive-Form Correlated Equilibrium
Gabriele Farina (Carnegie Mellon University) · Chun Kai Ling (Carnegie Mellon University) · Fei Fang (Carnegie Mellon University) · Tuomas Sandholm (CMU, Strategic Machine, Strategy Robot, Optimized Markets)

Learning in Generalized Linear Contextual Bandits with Stochastic Delays
Zhengyuan Zhou (Stanford University) · Renyuan Xu (University of Oxford) · Jose Blanchet (Stanford University)

Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness
Saeed Mahloujifar (University of Virginia) · Xiao Zhang (University of Virginia) · Mohammad Mahmoody (University of Virginia) · David Evans (University of Virginia)

Optimistic Regret Minimization for Extensive-Form Games via Dilated Distance-Generating Functions
Gabriele Farina (Carnegie Mellon University) · Christian Kroer (Columbia University) · Tuomas Sandholm (CMU, Strategic Machine, Strategy Robot, Optimized Markets)

On Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model
Erik Nijkamp (UCLA) · Mitch Hill (UCLA Department of Statistics) · Song-Chun Zhu (UCLA) · Ying Nian Wu (University of California, Los Angeles)

Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting
Shiyang Li (UCSB) · Xiaoyong Jin (UCSB) · Yao Xuan (University of California, Santa Barbara) · Xiyou Zhou (UCSB) · Wenhu Chen (University of California, Santa Barbara) · Yu-Xiang Wang (UC Santa Barbara) · Xifeng Yan (UCSB)

On the Accuracy of Influence Functions for Measuring Group Effects
Pang Wei Koh (Stanford University) · Kai-Siang Ang (Stanford University) · Hubert Teo (Stanford University) · Percy Liang (Stanford University)

Face Reconstruction from Voice using Generative Adversarial Networks
Yandong Wen (Carnegie Mellon University) · Bhiksha Raj (Carnegie Mellon University) · Rita Singh (Carnegie Mellon University)

Incremental Few-Shot Learning with Attention Attractor Networks
Mengye Ren (University of Toronto / Uber ATG) · Renjie Liao (University of Toronto) · Ethan Fetaya (University of Toronto) · Richard Zemel (Vector Institute/University of Toronto)

On Testing for Biases in Peer Review
Ivan Stelmakh (Carnegie Mellon University) · Nihar Shah (CMU) · Aarti Singh (CMU)

Learning Disentangled Representation for Robust Person Re-identification
Chanho Eom (Yonsei University) · Bumsub Ham (Yonsei University)

Balancing Efficiency and Fairness in On-Demand Ridesourcing
Nixie S Lesmana (Nanyang Technological University) · Xuan Zhang (University of Illinois at Champaign-Urbana) · Xiaohui Bei (Nanyang Technological University)

Latent Ordinary Differential Equations for Irregularly-Sampled Time Series
Yulia Rubanova (University of Toronto) · Tian Qi Chen (U of Toronto) · David Duvenaud (University of Toronto)

Deep RGB-D Canonical Correlation Analysis For Sparse Depth Completion
Yiqi Zhong (University of Southern California) · Cho-Ying Wu (Univ. of Southern California) · Suya You (US Army Research Laboratory) · Ulrich Neumann (USC)

Input Similarity from the Neural Network Perspective
Guillaume Charpiat (INRIA) · Nicolas Girard (Inria Sophia-Antipolis) · Loris Felardos (INRIA) · Yuliya Tarabalka (Inria Sophia-Antipolis)

Adaptive Sequence Submodularity
Marko Mitrovic (Yale University) · Ehsan Kazemi (Yale) · Moran Feldman (Open University of Israel) · Andreas Krause (ETH Zurich) · Amin Karbasi (Yale)

Weight Agnostic Neural Networks
Adam Gaier (Google / Inria / H-BRS) · David Ha (Google Brain)

Learning to Predict Without Looking Ahead: World Models Without Forward Prediction
Daniel Freeman (Google Brain) · David Ha (Google Brain) · Luke Metz (Google Brain)

Reducing the variance in online optimization by transporting past gradients
Sébastien Arnold (USC) · Pierre-Antoine Manzagol (Google) · Reza Harikandeh (UBC) · Ioannis Mitliagkas (Mila & University of Montreal) · Nicolas Le Roux (Google Brain)

Characterizing Bias in Classifiers using Generative Models
Daniel McDuff (Microsoft Research) · Shuang Ma (SUNY Buffalo) · Yale Song (Microsoft) · Ashish Kapoor (Microsoft)

Optimal Stochastic and Online Learning with Individual Iterates
Yunwen Lei (Technical University of Kaiserslautern) · Peng Yang (Southern University of Science and Technology) · Ke Tang (Southern University of Science and Technology) · Ding-Xuan Zhou (City University of Hong Kong)

Policy Learning for Fairness in Ranking
Ashudeep Singh (Cornell University) · Thorsten Joachims (Cornell)

Off-Policy Evaluation of Generalization for Deep Q-Learning in Binary Reward Tasks
Alexander Irpan (Google Brain) · Kanishka Rao (Google) · Konstantinos Bousmalis (DeepMind) · Chris Harris (Google) · Julian Ibarz (Google Inc.) · Sergey Levine (Google)

Regularized Gradient Boosting
Corinna Cortes (Google Research) · Mehryar Mohri (Courant Inst. of Math. Sciences & Google Research) · Dmitry Storcheus (Google Research)

Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
Atilim Gunes Baydin (University of Oxford) · Lei Shao (Intel Corporation) · Wahid Bhimji (Berkeley lab) · Lukas Heinrich (New York University) · Saeid Naderiparizi (University of British Columbia) · Andreas Munk (University of British Columbia) · Jialin Liu (Lawrence Berkeley National Lab) · Bradley Gram-Hansen (University of Oxford) · Gilles Louppe (University of Liège) · Lawrence Meadows (Intel Corporation) · Philip Torr (University of Oxford) · Victor Lee (Intel Corporation) · Kyle Cranmer (New York University) · Mr. Prabhat (LBL/NERSC) · Frank Wood (University of British Columbia)

Markov Random Fields for Collaborative Filtering
Harald Steck (Netflix)

A Step Toward Quantifying Independently Reproducible Machine Learning Research
Edward Raff (Booz Allen Hamilton)

Scalable Global Optimization via Local Bayesian Optimization
David Eriksson (Uber AI) · Matthias Poloczek (Uber AI) · Jacob Gardner (Uber AI Labs) · Ryan Turner (Uber AI Labs) · Michael Pearce (Warwick University)

Time-series Generative Adversarial Networks
Jinsung Yoon (University of California, Los Angeles) · Daniel Jarrett (University of Cambridge) · M Van Der Schaar (University of California, Los Angeles)

On Accelerating Training of Transformer-Based Language Models
Qian Yang (Duke University) · Zhouyuan Huo (University of Pittsburgh) · Wenlin Wang (Duke Univeristy) · Lawrence Carin (Duke University)

A Refined Margin Distribution Analysis for Forest Representation Learning
Shen-Huan Lyu (Nanjing University) · Liang Yang (Nanjing University) · Zhi-Hua Zhou (Nanjing University)

Robustness to Adversarial Perturbations in Learning from Incomplete Data
Amir Najafi (Sharif University of Technology) · Shin-ichi Maeda (Preferred Networks) · Masanori Koyama (Preferred Networks Inc. ) · Takeru Miyato (Preferred Networks, Inc.)

Exploring Unexplored Tensor Decompositions for Convolutional Neural Networks
Kohei Hayashi (Preferred Networks) · Taiki Yamaguchi (The University of Tokyo) · Yohei Sugawara (Preferred Networks, Inc.) · Shin-ichi Maeda (Preferred Networks)

An Adaptive Empirical Bayesian Method for Sparse Deep Learning
Wei Deng (Purdue University) · Xiao Zhang (Purdue University) · Faming Liang (Purdue University) · Guang Lin (Purdue University)

Adaptive Influence Maximization with Myopic Feedback
Binghui Peng (Tsinghua University) · Wei Chen (Microsoft Research)

Focused Quantization for Sparse CNNs
Yiren Zhao (University of Cambridge) · Xitong Gao (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences) · Daniel Bates (University of Cambridge) · Robert Mullins (University of Cambridge) · Cheng-Zhong Xu (University of Macau)

Quantum Embedding of Knowledge for Reasoning
Dinesh Garg (IBM Research AI, India) · Shajith Ikbal Mohamed (IBM Research AI, India) · Santosh Srivastava (IBM Research AI) · Harit Vishwakarma (IBM Research AI) · Hima Karanam (IBM Research AI) · L Venkat Subramaniam (IBM India Research Lab)

Optimal Best Markovian Arm Identification with Fixed Confidence
Vrettos Moulos (UC Berkeley)

Limiting Extrapolation in Linear Approximate Value Iteration
Andrea Zanette (Stanford University) · Alessandro Lazaric (Facebook Artificial Intelligence Research) · Mykel J Kochenderfer (Stanford University) · Emma Brunskill (Stanford University)

Almost Horizon-Free Structure-Aware Best Policy Identification with a Generative Model
Andrea Zanette (Stanford University) · Mykel J Kochenderfer (Stanford University) · Emma Brunskill (Stanford University)

Invertible Convolutional Flow
Mahdi Karami (University of Alberta) · Dale Schuurmans (Google) · Jascha Sohl-Dickstein (Google Brain) · Laurent Dinh (Google Brain) · Daniel Duckworth (Google Brain)

A Latent Variational Framework for Stochastic Optimization
Philippe Casgrain (University of Toronto)

Topology-Preserving Deep Image Segmentation
Xiaoling Hu (Stony Brook University) · Fuxin Li (Oregon State University) · Dimitris Samaras (Stony Brook University) · Chao Chen (Stony Brook University)

Connective Cognition Network for Directional Visual Commonsense Reasoning
Aming Wu (Tianjin University) · Linchao Zhu (University of Sydney, Technology) · Yahong Han (Tianjin University, China) · Yi Yang (UTS)

Online Markov Decoding: Lower Bounds and Near-Optimal Approximation Algorithms
Vikas Garg (MIT) · Tamar Pichkhadze (MIT)

A Meta-MDP Approach to Exploration for Lifelong Reinforcement Learning
Francisco Garcia (University of Massachusetts - Amherst) · Philip Thomas (University of Massachusetts Amherst)

Push-pull Feedback Implements Hierarchical Information Retrieval Efficiently
Xiao Liu (Peking University) · Xiaolong Zou (Peking University) · Zilong Ji (Beijing Normal University) · Gengshuo Tian (Beijing Normal University) · Yuanyuan Mi (Weizmann Institute of Science) · Tiejun Huang (Peking University) · K. Y. Michael Wong (Department of Physics, Hong Kong University of Science and Technology) · Si Wu (Peking University)

Learning Disentangled Representations for Recommendation
Jianxin Ma (Tsinghua University) · Chang Zhou (Alibaba Group) · Peng Cui (Tsinghua University) · Hongxia Yang (Alibaba Group) · Wenwu Zhu (Tsinghua University)

Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels
Simon Du (Institute for Advanced Study) · Kangcheng Hou (Zhejiang University) · Russ Salakhutdinov (Carnegie Mellon University) · Barnabas Poczos (Carnegie Mellon University) · Ruosong Wang (Carnegie Mellon University) · Keyulu Xu (MIT)

In-Place Near Zero-Cost Memory Protection for DNN
Hui Guan (North Carolina State University) · Lin Ning (NCSU) · Zhen Lin (NCSU) · Xipeng Shen (North Carolina State University) · Huiyang Zhou (NCSU) · Seung-Hwan Lim (Oak Ridge National Laboratory)

Acceleration via Symplectic Discretization of High-Resolution Differential Equations
Bin Shi (UC Berkeley) · Simon Du (Institute for Advanced Study) · Weijie Su (The Wharton School, University of Pennsylvania) · Michael Jordan (UC Berkeley)

XLNet: Generalized Autoregressive Pretraining for Language Understanding
Zhilin Yang (Recurrent AI) · Zihang Dai (Carnegie Mellon University) · Yiming Yang (CMU) · Jaime Carbonell (CMU) · Russ Salakhutdinov (Carnegie Mellon University) · Quoc V Le (Google)

Comparison Against Task Driven Artificial Neural Networks Reveals Functional Properties in Mouse Visual Cortex
Jianghong Shi (University of Washington) · Eric Shea-Brown (University of Washington) · Michael Buice (Allen Institute for Brain Science)

Mixtape: Breaking the Softmax Bottleneck Efficiently
Zhilin Yang (Recurrent AI) · Thang Luong (Google) · Russ Salakhutdinov (Carnegie Mellon University) · Quoc V Le (Google)

Variance Reduced Policy Evaluation with Smooth Function Approximation
Hoi-To Wai (Chinese University of Hong Kong) · Mingyi Hong (University of Minnesota) · Zhuoran Yang (Princeton University) · Zhaoran Wang (Northwestern University) · Kexin Tang (Shanghai Jiao Tong University)

Learning GANs and Ensembles Using Discrepancy
Ben Adlam (Google) · Corinna Cortes (Google Research) · Mehryar Mohri (Courant Inst. of Math. Sciences & Google Research) · Ningshan Zhang (New York University)

Co-Generation with GANs using AIS based HMC
Tiantian Fang (University of Illinois Urbana-Champaign) · Alexander Schwing (University of Illinois at Urbana-Champaign)

AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification
Ronghui You (Fudan University) · Zihan Zhang (Fudan University) · Ziye Wang (Fudan University) · Suyang Dai (Fudan University) · Hiroshi Mamitsuka (Kyoto University) · Shanfeng Zhu (Fudan University)

Addressing Sample Complexity in Visual Tasks Using HER and Hallucinatory GANs
Himanshu Sahni (Georgia Institute of Technology) · Toby Buckley (Offworld Inc.) · Pieter Abbeel (University of California, Berkley & OpenAI) · Ilya Kuzovkin (Offworld Inc.)

Abstract Reasoning with Distracting Features
Kecheng Zheng (University of Science and Technology of China) · Zheng-Jun Zha (University of Science and Technology of China) · Wei Wei (Google AI)

Generalized Block-Diagonal Structure Pursuit: Learning Soft Latent Task Assignment against Negative Transfer
Zhiyong Yang (SKLOIS, Institute of Information Engineering, Chinese Academy of Sciences; SCS, University of Chinese Academy of Sciences) · Qianqian Xu (Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences) · Yangbangyan Jiang (Institute of Information Engineering, Chinese Academy of Sciences) · Xiaochun Cao (Institute of Information Engineering, Chinese Academy of Sciences) · Qingming Huang (University of Chinese Academy of Sciences)

Adversarial Training and Robustness for Multiple Perturbations
Florian Tramer (Stanford University) · Dan Boneh (Stanford University)

Doubly-Robust Lasso Bandit
Gi-Soo Kim (Seoul National University) · Myunghee Cho Paik (Seoul National University)

DM2C: Deep Mixed-Modal Clustering
Yangbangyan Jiang (Institute of Information Engineering, Chinese Academy of Sciences) · Qianqian Xu (Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences) · Zhiyong Yang (SKLOIS, Institute of Information Engineering, Chinese Academy of Sciences; SCS, University of Chinese Academy of Sciences) · Xiaochun Cao (Institute of Information Engineering, Chinese Academy of Sciences) · Qingming Huang (University of Chinese Academy of Sciences)

MaCow: Masked Convolutional Generative Flow
Xuezhe Ma (Carnegie Mellon University) · Xiang Kong (Carnegie Mellon University) · Shanghang Zhang (Carnegie Mellon University) · Eduard Hovy (Carnegie Mellon University)

Learning by Abstraction: The Neural State Machine for Visual Reasoning
Drew Hudson (Stanford) · Christopher Manning (Stanford University)

Adaptive Gradient-Based Meta-Learning Methods
Mikhail Khodak (CMU) · Maria-Florina Balcan (Carnegie Mellon University) · Ameet Talwalkar (CMU)

Equipping Experts/Bandits with Long-term Memory
Kai Zheng (Peking University) · Haipeng Luo (University of Southern California) · Ilias Diakonikolas (USC) · Liwei Wang (Peking University)

A Regularized Approach to Sparse Optimal Policy in Reinforcement Learning
Wenhao Yang (Peking University) · Xiang Li (Peking University) · Zhihua Zhang (Peking University)

Scalable inference of topic evolution via models for latent geometric structures
Mikhail Yurochkin (IBM Research, MIT-IBM Watson AI Lab) · Zhiwei Fan (University of Wisconsin-Madison) · Aritra Guha (University of Michigan) · Paraschos Koutris (University of Wisconsin-Madison) · XuanLong Nguyen (University of Michigan)

Effective End-to-end Unsupervised Outlier Detection via Inlier Priority of Discriminative Network
Siqi Wang (National University of Defense Technology) · Yijie Zeng (Nanyang Technological University) · Xinwang Liu (National University of Defense Technology) · En Zhu (National University of Defense Technology) · Jianping Yin (Dongguan University of Technology) · Chuanfu Xu (National University of Defense Technology) · Marius Kloft (TU Kaiserslautern)

Deep Active Learning with a Neural Architecture Search
Yonatan Geifman (Technion) · Ran El-Yaniv (Technion)

Efficiently escaping saddle points on manifolds
Christopher Criscitiello (None, formerly Princeton University) · Nicolas Boumal (Princeton University)

AutoAssist: A Framework to Accelerate Training of Deep Neural Networks
Jiong Zhang (University of Texas at Austin) · Hsiang-Fu Yu (Amazon) · Inderjit S Dhillon (UT Austin & Amazon)

DFNets: Spectral CNNs for Graphs with Feedback-looped Filters
W. O. K. Asiri Suranga Wijesinghe (The Australian National University) · Qing Wang (Australian National University)

Learning Dynamics of Attention: Human Prior for Interpretable Machine Reasoning
Wonjae Kim (Kakao Corporation) · Yoonho Lee (Kakao Corporation)

Comparing Unsupervised Word Translation Methods Step by Step
Mareike Hartmann (University of Copenhagen) · Yova Kementchedjhieva (University of Copenhagen) · Anders Søgaard (University of Copenhagen)

Learning from Crap Data via Generation
Tianyu Guo (Peking University) · Chang Xu (University of Sydney) · Boxin Shi (Peking University) · Chao Xu (Peking University) · Dacheng Tao (University of Sydney)

Constrained deep neural network architecture search for IoT devices accounting hardware calibration
Florian Scheidegger (IBM Research -- Zurich) · Luca Benini (ETHZ, University of Bologna ) · Costas Bekas (IBM Research GmbH) · A. Cristiano I. Malossi (IBM Research - Zurich)

Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection
Yihe Dong (Microsoft Research) · Sam Hopkins (UC Berkeley) · Jerry Li (Microsoft)

Iterative Least Trimmed Squares for Mixed Linear Regression
Yanyao Shen (UT Austin) · Sujay Sanghavi (UT-Austin)

Dynamic Ensemble Modeling Approach to Nonstationary Neural Decoding in Brain-Computer Interfaces
Yu Qi (Zhejiang University) · Bin Liu (Nanjing University of Posts and Telecommunications) · Yueming Wang (Zhejiang University) · Gang Pan (Zhejiang University)

Divergence-Augmented Policy Optimization
Qing Wang (Huya AI) · Yingru Li (The Chinese University of Hong Kong, Shenzhen, China) · Jiechao Xiong (Tencent AI Lab) · Tong Zhang (Tencent AI Lab)

Intrinsic dimension of data representations in deep neural networks
Alessio Ansuini (International School for Advanced Studies (SISSA)) · Alessandro Laio (International School for Advanced Studies (SISSA)) · Jakob H Macke (Technical University of Munich, Munich, Germany) · Davide Zoccolan (Visual Neuroscience Lab, International School for Advanced Studies (SISSA))

Towards a Zero-One Law for Column Subset Selection
Zhao Song (University of Washington) · David Woodruff (Carnegie Mellon University) · Peilin Zhong (Columbia University)

Compositional De-Attention Networks
Yi Tay (Nanyang Technological University) · Anh Tuan Luu (MIT CSAIL) · Aston Zhang (Amazon AI) · Shuohang Wang (Singapore Management University) · Siu Cheung Hui (Nanyang Technological University)

Dual Adversarial Semantics-Consistent Network for Generalized Zero-Shot Learning
Jian Ni (University of Science and Technology of China) · Shanghang Zhang (Carnegie Mellon University) · Haiyong Xie (University of Science and Technology of China)

Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers
Zeyuan Allen-Zhu (Microsoft Research) · Yuanzhi Li (Princeton) · Yingyu Liang (University of Wisconsin Madison)

Mining GOLD Samples for Conditional GANs
Sangwoo Mo (KAIST) · Chiheon Kim (Kakao Brain) · Sungwoong Kim (Kakao Brain) · Minsu Cho (POSTECH) · Jinwoo Shin (KAIST; AITRICS)

Deep Model Transferability from Attribution Maps
Jie Song (Zhejiang University) · Yixin Chen (Zhejiang University) · Xinchao Wang (Stevens Institute of Technology) · Chengchao Shen (Zhejiang University) · Mingli Song (Zhejiang University)

Fully Parameterized Quantile Function for Distributional Reinforcement Learning
Derek Yang (UC San Diego) · Li Zhao (Microsoft Research) · Zichuan Lin (Tsinghua University) · Tao Qin (Microsoft Research) · Jiang Bian (Microsoft) · Tie-Yan Liu (Microsoft Research Asia)

Direct Optimization through
arg
max
arg⁡max for Discrete Variational Auto-Encoder
Guy Lorberbom (Technion) · Tommi Jaakkola (MIT) · Andreea Gane (Google AI) · Tamir Hazan (Technion)

Distributional Reward Decomposition for Reinforcement Learning
Zichuan Lin (Tsinghua University) · Li Zhao (Microsoft Research) · Derek Yang (UC San Diego) · Tao Qin (Microsoft Research) · Tie-Yan Liu (Microsoft Research Asia) · Guangwen Yang (Tsinghua University)

L_DMI: A Novel Information-theoretic Loss Function for Training Deep Nets Robust to Label Noise
Yilun Xu (Peking University) · Peng Cao (Peking University) · Yuqing Kong (Peking University) · Yizhou Wang (Peking University)

Convergence Guarantees for Adaptive Bayesian Quadrature Methods
Motonobu Kanagawa (EURECOM) · Philipp Hennig (University of Tübingen and MPI for Intelligent Systems Tübingen)

Progressive Augmentation of GANs
Dan Zhang (Bosch Center for Artificial Intelligence) · Anna Khoreva (Bosch Center for Artificial Intelligence)

UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization
Ali Kavis (EPFL) · Yehuda Kfir Levy (ETH) · Francis Bach (INRIA - Ecole Normale Superieure) · Volkan Cevher (EPFL)

Meta-Surrogate Benchmarking for Hyperparameter Optimization
Aaron Klein (Amazon Berlin) · Zhenwen Dai (Spotify) · Frank Hutter (University of Freiburg) · Neil Lawrence (Amazon) · Javier Gonzalez (Amazon)

Learning to Perform Local Rewriting for Combinatorial Optimization
Xinyun Chen (UC Berkeley) · Yuandong Tian (Facebook AI Research)

Anti-efficient encoding in emergent communication
Rahma Chaabouni (FAIR/ENS) · Eugene Kharitonov (Facebook AI) · Emmanuel Dupoux (Ecole des Hautes Etudes en Sciences Sociales) · Marco Baroni (University of Trento)

Singleshot : a scalable Tucker tensor decomposition
Abraham Traore () · Maxime Berar (Université de Rouen) · Alain Rakotomamonjy (Université de Rouen Normandie Criteo AI Lab)

Neural Machine Translation with Soft Prototype
Yiren Wang (University of Illinois at Urbana-Champaign) · Yingce Xia (Microsoft Research Asia) · Fei Tian (Facebook) · Fei Gao (University of Chinese Academy of Sciences) · Tao Qin (Microsoft Research) · Cheng Xiang Zhai (University of Illinois at Urbana-Champaign) · Tie-Yan Liu (Microsoft Research)

Reliable training and estimation of variance networks
Nicki Skafte Detlefsen (Technical University of Denmark) · Martin Jørgensen (Technical University of Denmark) · Søren Hauberg (Technical University of Denmark)

On the Statistical Properties of Multilabel Learning
Weiwei Liu (Wuhan University)

Bayesian Learning of Sum-Product Networks
Martin Trapp (Graz University of Technology) · Robert Peharz (University of Cambridge) · Hong Ge (University of Cambridge) · Franz Pernkopf (Signal Processing and Speech Communication Laboratory, Graz, Austria) · Zoubin Ghahramani (Uber and University of Cambridge)

Bayesian Batch Active Learning as Sparse Subset Approximation
Robert Pinsler (University of Cambridge) · Jonathan Gordon (University of Cambridge) · Eric Nalisnick (University of Cambridge) · José Miguel Hernández-Lobato (University of Cambridge)

Optimal Sparsity-Sensitive Bounds for Distributed Mean Estimation
zengfeng Huang (Fudan University) · Ziyue Huang (HKUST) · Yilei WANG (The Hong Kong University of Science and Technology) · Ke Yi (" Hong Kong University of Science and Technology, Hong Kong")

Global Sparse Momentum SGD for Pruning Very Deep Neural Networks
Xiaohan Ding (Tsinghua University) · guiguang ding (Tsinghua University, China) · Xiangxin Zhou (Tsinghua University) · Yuchen Guo (Tsinghua University) · Jungong Han (Lancaster University) · Ji Liu (University of Rochester, Tencent AI lab)

Variational Bayesian Decision-making for Continuous Utilities
Tomasz Kuśmierczyk (University of Helsinki) · Joseph Sakaya (University of Helsinki) · Arto Klami (University of Helsinki)

The Normalization Method for Alleviating Pathological Sharpness in Wide Neural Networks
Ryo Karakida (National Institute of Advanced Industrial Science and Technology) · Shotaro Akaho (AIST) · Shun-ichi Amari (RIKEN)

Single-Model Uncertainties for Deep Learning
Natasa Tagasovska (University of Lausanne) · David Lopez-Paz (Facebook AI Research)

Is Deeper Better only when Shallow is Good?
Eran Malach (Hebrew University Jerusalem Israel) · Shai Shalev-Shwartz (Mobileye & HUJI)

Wasserstein Weisfeiler-Lehman Graph Kernels
Matteo Togninalli (ETH Zürich) · Elisabetta Ghisu (ETH Zurich) · Felipe Llinares-Lopez (ETH Zürich) · Bastian Rieck (MLCB, D-BSSE, ETH Zurich) · Karsten Borgwardt (ETH Zurich)

Domain Generalization via Model-Agnostic Learning of Semantic Features
Qi Dou (Imperial College London) · Daniel Coelho de Castro (Imperial College London) · Konstantinos Kamnitsas (Imperial College London) · Ben Glocker (Imperial College London)

Grid Saliency for Context Explanations of Semantic Segmentation
Lukas Hoyer (Bosch Center for Artificial Intelligence) · Mauricio Munoz (Bosch Center for Artificial Intelligence) · Prateek Katiyar (Bosch Center for Artificial Intelligence) · Anna Khoreva (Bosch Center for Artificial Intelligence) · Volker Fischer (Robert Bosch GmbH, Bosch Center for Artificial Intelligence)

First-order methods almost always avoid saddle points: The case of Vanishing step-sizes
Ioannis Panageas (SUTD) · Georgios Piliouras (Singapore University of Technology and Design) · Xiao Wang (Singapore University of Technology and Design)

Maximum Mean Discrepancy Gradient Flow
Michael Arbel (UCL) · Anna Korba (UCL) · Adil SALIM (KAUST) · Arthur Gretton (Gatsby Unit, UCL)

Oblivious Sampling Algorithms for Private Data Analysis
Olga Ohrimenko (Microsoft Research) · Sajin Sasy (University of Waterloo)

Semi-supervisedly Co-embedding Attributed Networks
Zai Qiao Meng (University of Glasgow) · Shangsong Liang (Sun Yat-sen University) · Jinyuan Fang (Sun Yat-sen University) · Teng Xiao (Sun Yat-sen University)

From voxels to pixels and back: Self-supervision in natural-image reconstruction from fMRI
Roman Beliy (weizmann institute) · Guy Gaziv (Weizmann Institute of Science) · Assaf Hoogi (Weizmann Institute) · Francesca Strappini (Weizmann Institute of Science) · Tal Golan (Columbia University) · Michal Irani (Weizmann Institute of Science)

Copulas as High-Dimensional Generative Models: Vine Copula Autoencoders
Natasa Tagasovska (University of Lausanne) · Damien Ackerer (Swissquote) · Thibault Vatter (Columbia University)

Nonstochastic Multiarmed Bandits with Unrestricted Delays
Tobias Sommer Thune (University of Copenhagen) · Nicolò Cesa-Bianchi (Università degli Studi di Milano) · Yevgeny Seldin (University of Copenhagen)

BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling
Lars Maaløe (Corti) · Marco Fraccaro (Unumed) · Valentin Liévin (DTU) · Ole Winther (Technical University of Denmark)

Code Generation as Dual Task of Code Summarization
Bolin Wei (Peking University) · Ge Li (Peking University) · Xin Xia (Monash University) · Zhiyi Fu (Key Lab of High Confidence Software Technologies (Peking University), Ministry of Education) · Zhi Jin (Key Lab of High Confidence Software Technologies (Peking University), Ministry o)

Diffeomorphic Temporal Alignment Networks
Ron A Shapira Weber (Ben-Gurion University) · Matan Eyal (Ben Gurion University) · Nicki Skafte Detlefsen (Technical University of Denmark) · Oren Shriki (Ben-Gurion University of the Negev) · Oren Freifeld (Ben-Gurion University)

Weakly Supervised Instance Segmentation using the Bounding Box Tightness Prior
Cheng-Chun Hsu (Academia Sinica) · Kuang-Jui Hsu (Qualcomm) · Chung-Chi Tsai (Qualcomm) · Yen-Yu Lin (National Chiao Tung University) · Yung-Yu Chuang (National Taiwan University)

On the Power and Limitations of Random Features for Understanding Neural Networks
Gilad Yehudai (Weizmann Institute of Science) · Ohad Shamir (Weizmann Institute of Science)

Efficient Pure Exploration in Adaptive Round model
tianyuan jin (University of Science and Technology of China) · Jieming SHI (NATIONAL UNIVERSITY OF SINGAPORE) · Xiaokui Xiao (National University of Singapore) · Enhong Chen (University of Science and Technology of China)

Multi-objects Generation with Amortized Structural Regularization
Taufik Xu (Tsinghua University) · Chongxuan LI (Tsinghua University) · Jun Zhu (Tsinghua University) · Bo Zhang (Tsinghua University)

Neural Shuffle-Exchange Networks - Sequence Processing in O(n log n) Time
Karlis Freivalds (Institute of Mathematics and Computer Science, University of Latvia) · Emīls Ozoliņš (Institute of Mathematics and Computer Science) · Agris Šostaks (Institute of Mathematics and Computer Science)

DetNAS: Backbone Search for Object Detection
Yukang Chen (Institute of Automation, Chinese Academy of Sciences) · Tong Yang (Megvii Inc.) · Xiangyu Zhang (MEGVII Technology) · GAOFENG MENG (Institute of Automation, Chinese Academy of Sciences) · Xinyu Xiao (National Laboratory of Pattern recognition (NLPR), Institute of Automation of Chinese Academy of Sciences (CASIA)) · Jian Sun (Megvii, Face++)

Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates
Adil SALIM (KAUST) · Dmitry Koralev (KAUST) · Peter Richtarik (KAUST)

Fast AutoAugment
Sungbin Lim (Kakao Brain) · Ildoo Kim (Kakao Brain) · Taesup Kim (Mila / Kakao Brain) · Chiheon Kim (Kakao Brain) · Sungwoong Kim (Kakao Brain)

On the Convergence Rate of Training Recurrent Neural Networks in the Overparameterized Regime
Zeyuan Allen-Zhu (Microsoft Research) · Yuanzhi Li (Princeton) · Zhao Song (University of Washington)

Interval timing in deep reinforcement learning agents
Ben Deverett (Princeton University) · Ryan Faulkner (Deepmind) · Meire Fortunato (DeepMind) · Gregory Wayne (Google DeepMind) · Joel Leibo (DeepMind)

Graph-based Discriminators: Sample Complexity and Expressiveness
Roi Livni (Tel Aviv University) · Yishay Mansour (Tel Aviv University / Google)

Large Scale Structure of Neural Network Loss Landscapes
Stanislav Fort (Stanford University) · Stanislaw Jastrzebski (New York University)

Learning Nonsymmetric Determinantal Point Processes
Mike Gartrell (Criteo AI Lab) · Victor-Emmanuel Brunel (ENSAE ParisTech) · Elvis Dohmatob (Criteo) · Syrine Krichene (Google)

Hypothesis Set Stability and Generalization
Dylan Foster (MIT) · Spencer Greenberg (Spark Wave) · Satyen Kale (Google) · Haipeng Luo (University of Southern California) · Mehryar Mohri (Courant Inst. of Math. Sciences & Google Research) · Karthik Sridharan (Cornell University)

Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds
Bo Yang (University of Oxford) · Jianan Wang (DeepMind) · Ronald Clark (Imperial College London) · Qingyong Hu (University of Oxford) · Sen Wang (Heriot-Watt University) · Andrew Markham (University of Oxford) · Niki Trigoni (University of Oxford)

Precision-Recall Balanced Topic Modelling
Seppo Virtanen (Imperial College London) · Mark Girolami (Imperial College London)

Learning Sparse Distributions using Iterative Hard Thresholding
Yibo Zhang (Illinois) · Rajiv Khanna (University of California at Berkeley) · Anastasios Kyrillidis (Rice University) · Oluwasanmi Koyejo (UIUC)

Discriminative Topic Modeling with Logistic LDA
Iryna Korshunova (Ghent University) · Hanchen Xiong (Twitter) · Mateusz Fedoryszak (Twitter) · Lucas Theis (Twitter)

Quantum Wasserstein Generative Adversarial Networks
Shouvanik Chakrabarti (University of Maryland) · Huang Yiming (University of Electronic Science and Technology of China; University of Maryland) · Tongyang Li (University of Maryland) · Soheil Feizi (University of Maryland) · Xiaodi Wu (University of Maryland)

Blow: a single-scale hyperconditioned flow for non-parallel raw-audio voice conversion
Joan Serrà (Telefónica Research) · Santiago Pascual (Universitat Politècnica de Catalunya) · Carlos Segura Perales (Telefónica Research)

Hyperparameter Learning via Distributional Transfer
Ho Chung Law (University of Oxford) · Peilin Zhao (Tencent AI Lab) · Lucian Chan (University of Oxford) · Junzhou Huang (University of Texas at Arlington / Tencent AI Lab) · Dino Sejdinovic (University of Oxford)

Discriminator optimal transport
Akinori Tanaka (RIKEN/Keio Univ.)

High-dimensional multivariate forecasting with low-rank Gaussian Copula Processes
David Salinas (Naverlabs) · Michael Bohlke-Schneider (Amazon) · Laurent Callot (Amazon) · Jan Gasthaus (Amazon.com) · Roberto Medico (Ghent University)

Are Anchor Points Really Indispensable in Label-Noise Learning?
Xiaobo Xia (The University of Sydney / Xidian University) · Tongliang Liu (The University of Sydney) · Nannan Wang (Xidian University) · Bo Han (RIKEN) · Chen Gong (Nanjing University of Science and Technology) · Gang Niu (RIKEN) · Masashi Sugiyama (RIKEN / University of Tokyo)

Aligning Visual Regions and Textual Concepts for Semantic-Grounded Image Representations
Fenglin Liu (Peking University) · Yuanxin Liu (Institute of Information Engineering, Chinese Academy of Sciences) · Xuancheng Ren (Peking University) · Xiaodong He (JD AI research) · Kai Lei (peking university) · Xu Sun (Peking University)

Differentiable Sorting using Optimal Transport: The Sinkhorn CDF and Quantile Operator
Marco Cuturi (Google and CREST/ENSAE) · Olivier Teboul (Google Brain) · Jean-Philippe Vert ()

Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks
Gaël Letarte (Université Laval) · Pascal Germain (INRIA) · Benjamin Guedj (Inria & University College London) · Francois Laviolette (Université Laval)

Likelihood-Free Overcomplete ICA and ApplicationsIn Causal Discovery
Chenwei DING (The University of Sydney) · Mingming Gong (University of Melbourne) · Kun Zhang (CMU) · Dacheng Tao (University of Sydney)

Interior-point Methods Strike Back: Solving the Wasserstein Barycenter Problem
DongDong Ge (Shanghai University of Finance and Economics) · Haoyue Wang (Fudan University) · Zikai Xiong (Fudan University) · Yinyu Ye (Standord)

Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs
Denis Mazur (Yandex) · Vage Egiazarian (Skoltech) · Stanislav Morozov (Yandex) · Artem Babenko (Yandex)

Subspace Detours: Building Transport Plans that are Optimal on Subspace Projections
Boris Muzellec (ENSAE, Institut Polytechnique de Paris) · Marco Cuturi (Google and CREST/ENSAE)

Efficient Non-Convex Stochastic Compositional Optimization Algorithm via Stochastic Recursive Gradient Descent
Huizhuo Yuan (Peking University) · Xiangru Lian (University of Rochester) · Chris Junchi Li (UC Berkeley) · Ji Liu (University of Rochester, Tencent AI lab)

On the convergence of single-call stochastic extra-gradient methods
Yu-Guan Hsieh (LJK; Université Grenoble Alpes; École Normale Supérieure Paris) · Franck Iutzeler (Univ. Grenoble Alpes) · Jérôme Malick (CNRS and LJK) · Panayotis Mertikopoulos (CNRS (French National Center for Scientific Research))

Infra-slow brain dynamics as a marker for cognitive function and decline
Shagun Ajmera (Indian Institute of Science) · Shreya Rajagopal (Indian Institute of Science) · Razi Rehman (Indian Institute of Science) · Devarajan Sridharan (Indian Institute of Science)

Robust Principle Component Analysis with Adaptive Neighbors
Rui Zhang (Northwestern Polytechincal University) · Hanghang Tong (IBM Research)

High-Quality Self-Supervised Deep Image Denoising
Samuli Laine (NVIDIA) · Tero Karras (NVIDIA) · Jaakko Lehtinen (Aalto University & NVIDIA) · Timo Aila (NVIDIA)

Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup
Sebastian Goldt (Institut de Physique Théorique, CNRS, Paris) · Madhu Advani (Apple) · Andrew Saxe (University of Oxford) · Florent Krzakala (École Normale Supérieure) · Lenka Zdeborová (CEA Saclay)

GIFT: Learning Transformation-Invariant Dense Visual Descriptors via Group CNNs
Yuan Liu (Zhejiang University) · Zehong Shen (Zhejiang University) · Zhixuan Lin (Zhejiang University) · Sida Peng (Zhejiang University) · Hujun Bao (Zhejiang University) · Xiaowei Zhou (Zhejiang University, China)

Online Prediction of Switching Graph Labelings with Cluster Specialists
Mark Herbster (University College London) · James Robinson (UCL)

Graph-Based Semi-Supervised Learning with Non-ignorable Non-response
Fan Zhou (Shanghai University of Finance and Economics) · Tengfei Li (UNC Chapel Hill) · Haibo Zhou (University of North Carolina at Chapel Hill) · Hongtu Zhu (UNC Chapel Hill) · Ye Jieping (DiDi Chuxing)

BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning
Andreas Kirsch (University of Oxford) · Joost van Amersfoort (University of Oxford) · Yarin Gal (University of Oxford)

A Mean Field Theory of Quantized Deep Networks: The Quantization-Depth Trade-Off
Yaniv Blumenfeld (Technion) · Dar Gilboa (Columbia University) · Daniel Soudry (Technion)

Beyond Confidence Regions: Tight Bayesian Ambiguity Sets for Robust MDPs
Marek Petrik (University of New Hampshire) · Reazul Hasan Russel (University of New Hampshire)

Cross-lingual Language Model Pretraining
Alexis CONNEAU (Facebook) · Guillaume Lample (Facebook AI Research)

Approximate Bayesian Inference for a Mechanistic Model of Vesicle Release at a Ribbon Synapse
Cornelius Schröder (University of Tübingen) · Ben James (University of Sussex) · Leon Lagnado (University of Sussex) · Philipp Berens (University of Tübingen)

Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input
Maxence Ernoult (Université Paris Sud) · Benjamin Scellier (Mila, University of Montreal) · Yoshua Bengio (Mila) · Damien Querlioz (Univ Paris-Sud) · Julie Grollier (Unité Mixte de Physique CNRS/Thales)

Universal Invariant and Equivariant Graph Neural Networks
Nicolas Keriven (Ecole Normale Supérieure) · Gabriel Peyré (CNRS and ENS)

The bias of the sample mean in multi-armed bandits can be positive or negative
Jaehyeok Shin (Carnegie Mellon University) · Aaditya Ramdas (Carnegie Mellon University) · Alessandro Rinaldo (CMU)

On the Correctness and Sample Complexity of Inverse Reinforcement Learning
Abi Komanduru (Purdue University) · Jean Honorio (Purdue University)

VIREL: A Variational Inference Framework for Reinforcement Learning
Matthew Fellows (University of Oxford) · Anuj Mahajan (University of Oxford) · Tim G. J. Rudner (University of Oxford) · Shimon Whiteson (University of Oxford)

First Order Motion Model for Image Animation
Aliaksandr Siarohin (University of Trento) · Stephane Lathuillere (University of Trento) · Sergey Tulyakov (Snap Inc) · Elisa Ricci (FBK - Technologies of Vision) · Nicu Sebe (University of Trento)

Tensor Monte Carlo: Particle Methods for the GPU era
Laurence Aitchison (University of Cambridge)

Unsupervised Emergence of Egocentric Spatial Structure from Sensorimotor Prediction
Alban Laflaquière (SoftBank Robotics Europe) · Michael Garcia Ortiz (SoftBank Robotics Europe)

Learning from Label Proportions with Generative Adversarial Networks
Jiabin Liu (University of Chinese Academy of Sciences) · Bo Wang (University of International Business and Economics) · Zhiquan Qi (University of Chinese Academy of Sciences) · YingJie Tian (University of Chinese Academy of Sciences) · Yong Shi (University of Chinese Academy of Sciences)

Efficient and Thrifty Voting by Any Means Necessary
Debmalya Mandal (Columbia University) · Ariel Procaccia (Carnegie Mellon University) · Nisarg Shah (University of Toronto) · David Woodruff (Carnegie Mellon University)

PointDAN: A Multi-Scale 3D Domain Adaption Network for Point Cloud Representation
Can Qin (Northeastern University) · Haoxuan You (Columbia University) · Lichen Wang (Northeastern University) · C.-C. Jay Kuo (University of Southern California) · Yun Fu (Northeastern University)

ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization
Xiangyi Chen (University of Minnesota) · Sijia Liu (MIT-IBM Watson AI Lab, IBM Research AI) · Kaidi Xu (Northeastern University) · Xingguo Li (Princeton University) · Xue Lin (Northeastern University) · Mingyi Hong (University of Minnesota) · David Cox (MIT-IBM Watson AI Lab)

Non-Stationary Markov Decision Processes, a Worst-Case Approach using Model-Based Reinforcement Learning
Erwan Lecarpentier (Université de Toulouse, ONERA The French Aerospace Lab) · Emmanuel Rachelson (ISAE-SUPAERO / University of Toulouse)

Depth-First Proof-Number Search with Heuristic Edge Cost and Application to Chemical Synthesis Planning
Akihiro Kishimoto (IBM Research) · Beat Buesser (IBM Research) · Bei Chen (IBM Research) · Adi Botea (IBM Research)

Toward a Characterization of Loss Functions for Distribution Learning
Nika Haghtalab (Cornell University) · Cameron Musco (Microsoft Research) · Bo Waggoner (U. Colorado, Boulder)

Coresets for Archetypal Analysis
Sebastian Mair (Leuphana University) · Ulf Brefeld (Leuphana)

Emergence of Object Segmentation in Perturbed Generative Models
Adam Bielski (University of Bern) · Paolo Favaro (Bern University, Switzerland)

Optimal Sparse Decision Trees
Xiyang Hu (Duke University) · Cynthia Rudin (Duke) · Margo Seltzer (University of British Columbia)

Escaping from saddle points on Riemannian manifolds
Yue Sun (University of Washington) · Nicolas Flammarion (EPFL) · Maryam Fazel (University of Washington)

Muti-source Domain Adaptation for Semantic Segmentation
Sicheng Zhao (University of California Berkeley) · Bo Li (Harbin Institute of Technology) · Xiangyu Yue (UC Berkeley) · Yang Gu (Didi chuxing) · Pengfei Xu (Didi Chuxing) · Runbo Hu (DiDi Chuxing) · Hua Chai (Didi Chuxing) · Kurt Keutzer (EECS, UC Berkeley)

Localized Structured Prediction
Carlo Ciliberto (Imperial College London) · Francis Bach (INRIA - Ecole Normale Superieure) · Alessandro Rudi (INRIA, Ecole Normale Superieure)

Nonzero-sum Adversarial Hypothesis Testing Games
Sarath Yasodharan (Indian Institute of Science) · Patrick Loiseau (Inria)

Manifold-regression to predict from MEG/EEG brain signals without source modeling
David Sabbagh (INRIA) · Pierre Ablin (Inria) · Gael Varoquaux (Parietal Team, INRIA) · Alexandre Gramfort (INRIA) · Denis A. Engemann (INRIA Saclay)

Modeling Tabular data using Conditional GAN
Lei Xu (Massachusetts Institute of Technology) · Maria Skoularidou (University of Cambridge) · Alfredo Cuesta Infante (Universidad Rey Juan Carlos) · Kalyan Veeramachaneni (Massachusetts Institute of Technology)

Normalization Helps Training of Quantized LSTM
Lu Hou (Huawei Technologies Co., Ltd) · Jinhua Zhu (University of Science and Technology of China) · James Kwok (Hong Kong University of Science and Technology) · Fei Gao (University of Chinese Academy of Sciences) · Tao Qin (Microsoft Research) · Tie-Yan Liu (Microsoft Research)

Trajectory of Alternating Direction Method of Multipliers and Adaptive Acceleration
Clarice Poon (University of Bath) · Jingwei Liang (University of Cambridge)

Deep Scale-spaces: Equivariance Over Scale
Daniel Worrall (University of Amsterdam) · Max Welling (University of Amsterdam / Qualcomm AI Research)

GRU-ODE-Bayes: Continuous Modeling of Sporadically-Observed Time Series
Edward De Brouwer (KU Leuven) · Jaak Simm (KU Leuven) · Adam Arany (University of Leuven) · Yves Moreau (KU Leuven)

Estimating Convergence of Markov chains with L-Lag Couplings
Niloy Biswas (Harvard University) · Pierre E Jacob (Harvard University)

Learning-Based Low-Rank Approximations
Piotr Indyk (MIT) · Ali Vakilian (University of Wisconsin-Madison) · Yang Yuan (Cornell University)

Implicit Regularization in Deep Matrix Factorization
Sanjeev Arora (Princeton University) · Nadav Cohen (Tel Aviv University) · Wei Hu (Princeton University) · Yuping Luo (Princeton University)

List-decodable Linear Regression
Sushrut Karmalkar (The University of Texas at Austin) · Adam Klivans (UT Austin) · Pravesh Kothari (Princeton University and Institute for Advanced Study)

Learning elementary structures for 3D shape generation and matching
Theo Deprelle (École des ponts ParisTech) · Thibault Groueix (École des ponts ParisTech) · Matthew Fisher (Adobe Research) · Vladimir Kim (Adobe) · Bryan Russell (Adobe) · Mathieu Aubry (École des ponts ParisTech)

On the Hardness of Robust Classification
Pascale Gourdeau (University of Oxford) · Varun Kanade (University of Oxford) · Marta Kwiatkowska (University of Oxford) · James Worrell (University of Oxford)

Foundations of Comparison-Based Hierarchical Clustering
Debarghya Ghoshdastidar (University of Tübingen) · Michaël Perrot (Max Planck Institute for Intelligent Systems) · Ulrike von Luxburg (University of Tübingen)

What the Vec? Towards Probabilistically Grounded Embeddings
Carl Allen (University of Edinburgh) · Ivana Balazevic (University of Edinburgh) · Timothy Hospedales (University of Edinburgh)

Minimizers of the Empirical Risk and Risk Monotonicity
Marco Loog (Delft University of Technology) · Tom Viering (Delft University of Technology, Netherlands) · Alexander Mey (TU Delft)

Explicit Planning for Efficient Exploration in Reinforcement Learning
Liangpeng Zhang (University of Birmingham) · Xin Yao (University of Birmingham)

Lower Bounds on Adversarial Robustness from Optimal Transport
Arjun Nitin Bhagoji (Princeton University) · Daniel Cullina (Princeton University) · Prateek Mittal (Princeton University)

Neural Spline Flows
Conor Durkan (University of Edinburgh) · Artur Bekasov (University of Edinburgh) · Iain Murray (University of Edinburgh) · George Papamakarios (DeepMind)

Phase Transitions and Cyclic Phenomena in Bandits with Switching Constraints
David Simchi-Levi (MIT) · Yunzong Xu (MIT)

Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization
Koen Helwegen (Plumerai) · James Widdicombe (Plumerai) · Lukas Geiger (Plumerai) · Zechun Liu (HKUST) · Kwang-Ting Cheng (Hong Kong University of Science and Technology) · Roeland Nusselder (Plumerai)

Nonlinear scaling of resource allocation in sensory bottlenecks
Laura Rose Edmondson (University of Sheffield) · Alejandro Jimenez Rodriguez (University of Sheffield) · Hannes P. Saal (University of Sheffield)

Constrained Reinforcement Learning: A Dual Approach
Santiago Paternain (University of Pennsylvania) · Luiz Chamon (University of Pennsylvania) · Miguel Calvo-Fullana (University of Pennsylvania) · Alejandro Ribeiro (University of Pennsylvania)

Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules
Niklas Gebauer (Technische Universität Berlin) · Michael Gastegger (Technische Universität Berlin) · Kristof Schütt (TU Berlin)

An adaptive nearest neighbor rule for classification
Akshay Balsubramani (Stanford) · Sanjoy Dasgupta (UC San Diego) · yoav Freund (UCSD) · Shay Moran (Google AI Princeton)

Coresets for Clustering with Fairness Constraints
Lingxiao Huang (EPFL) · Shaofeng Jiang (Weizmann Institute of Science) · Nisheeth Vishnoi (Yale University)

PerspectiveNet: A Scene-consistent Image Generator for New View Synthesis in Real Indoor Environments
Ben Graham (Facebook Research) · David Novotny (Facebook AI Research) · Jeremy Reizenstein (Facebook AI Research)

MAVEN: Multi-Agent Variational Exploration
Anuj Mahajan (University of Oxford) · Tabish Rashid (University of Oxford) · Mikayel Samvelyan (Russian-Armenian University) · Shimon Whiteson (University of Oxford)

Competitive Gradient Descent
Florian Schaefer (Caltech) · Anima Anandkumar (NVIDIA / Caltech)

Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses
Ulysse Marteau-Ferey (INRIA) · Francis Bach (INRIA - Ecole Normale Superieure) · Alessandro Rudi (INRIA, Ecole Normale Superieure)

Continual Unsupervised Representation Learning
Dushyant Rao (DeepMind) · Francesco Visin (DeepMind) · Andrei Rusu (DeepMind) · Razvan Pascanu (Google DeepMind) · Yee Whye Teh (University of Oxford, DeepMind) · Raia Hadsell (DeepMind)

Self-Routing Capsule Networks
Taeyoung Hahn (SNUVL) · Myeongjang Pyeon (Seoul National University) · Gunhee Kim (Seoul National University)

The Parameterized Complexity of Cascading Portfolio Scheduling
Eduard Eiben (University of Bergen) · Robert Ganian (TU Wien) · Iyad Kanj (DePaul University, Chicago) · Stefan Szeider (Vienna University of Technology)

Maximum Expected Hitting Cost of a Markov Decision Process and Informativeness of Rewards
Falcon Dai (TTI-Chicago) · Matthew Walter (TTI-Chicago)

Bipartite expander Hopfield networks as self-decoding high-capacity error correcting codes
Rishidev Chaudhuri (University of California, Davis) · Ila Fiete (University of Texas at Austin)

Sequence Modelling with Unconstrained Generation Order
Dmitrii Emelianenko (Yandex; National Research University Higher School of Economics) · Elena Voita (Yandex; University of Amsterdam) · Pavel Serdyukov (Yandex)

Probabilistic Logic Neural Networks for Reasoning
Meng Qu (Mila) · Jian Tang (HEC Montreal & MILA)

A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families
Brian Axelrod (Stanford) · Ilias Diakonikolas (USC) · Alistair Stewart (University of Southern California) · Anastasios Sidiropoulos (University of Illinois at Chicago) · Gregory Valiant (Stanford University)

A Unifying Framework for Spectrum-Preserving Graph Sparsification and Coarsening
Gecia Bravo Hermsdorff (Princeton University) · Lee Gunderson (Princeton University)

Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond
Xuechen Li (Google) · Yi Wu (University of Toronto & Vector Institute) · Lester Mackey (Microsoft Research) · Murat Erdogdu (University of Toronto)

The Implicit Bias of AdaGrad on Separable Data
Qian Qian (Ohio State University) · Xiaoyuan Qian (Dalian University of Technology)

On two ways to use determinantal point processes for Monte Carlo integration
Guillaume Gautier (CNRS, INRIA, Univ. Lille) · Rémi Bardenet (University of Lille) · Michal Valko (DeepMind Paris and Inria Lille - Nord Europe)

LiteEval: A Coarse-to-Fine Framework for Resource Efficient Video Recognition
Zuxuan Wu (University of Maryland) · Caiming Xiong (Salesforce) · Yu-Gang Jiang (Fudan University) · Larry Davis (University of Maryland)

How degenerate is the parametrization of neural networks with the ReLU activation function?
Dennis Maximilian Elbrächter (University of Vienna) · Julius Berner (University of Vienna) · Philipp Grohs (University of Vienna)

Spike-Train Level Backpropagation for Training Deep Recurrent Spiking Neural Networks
Wenrui Zhang (Texas A&M University) · Peng Li (University of California, Santa Barbara)

Re-examination of the Role of Latent Variables in Sequence Modeling
Guokun Lai (Carnegie Mellon University) · Zihang Dai (Carnegie Mellon University)

Max-value Entropy Search for Multi-Objective Bayesian Optimization
Syrine Belakaria (Washington State University) · Aryan Deshwal (Washington State University) · Janardhan Rao Doppa (Washington State University)

Stein Variational Gradient Descent With Matrix-Valued Kernels
Dilin Wang (UT Austin) · Ziyang Tang (UT Austin) · Chandrajit Bajaj (The University of Texas at Austin) · Qiang Liu (UT Austin)

Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms
Shahana Ibrahim (Oregon State University) · Xiao Fu (Oregon State University) · Nikolaos Kargas (University of Minnesota) · Kejun Huang (University of Florida)

Detecting Overfitting via Adversarial Examples
Roman Werpachowski (DeepMind) · András György (DeepMind) · Csaba Szepesvari (DeepMind/University of Alberta)

A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment
Felix Leibfried (PROWLER.io) · Sergio Pascual-Diaz (PROWLER.io) · Jordi Grau-Moya (PROWLER.io)

SMILe: Scalable Meta Inverse Reinforcement Learning through Context-Conditional Policies
Seyed Kamyar Seyed Ghasemipour (University of Toronto, Vector Institute) · Shixiang (Shane) Gu (Google Brain) · Richard Zemel (Vector Institute/University of Toronto)

Towards Understanding the Importance of Shortcut Connections in Residual Networks
Tianyi Liu (Georgia Institute of Technolodgy) · Minshuo Chen (Georgia Tech) · Mo Zhou (Duke University) · Simon Du (Institute for Advanced Study) · Enlu Zhou (Georgia Institute of Technology) · Tuo Zhao (Gatech)

Modular Universal Reparameterization: Deep Multi-task Learning Across Diverse Domains
Elliot Meyerson (Cognizant) · Risto Miikkulainen (The University of Texas at Austin; Cognizant)

Solving Interpretable Kernel Dimensionality Reduction
Chieh Wu (Northeastern University) · Jared Miller (Northeastern University) · Yale Chang (Northeastern University) · Mario Sznaier (Northeastern University) · Jennifer Dy (Northeastern University)

Interaction Hard Thresholding: Consistent Sparse Quadratic Regression in Sub-quadratic Time and Space
Shuo Yang (UT Austin) · Yanyao Shen (UT Austin) · Sujay Sanghavi (UT-Austin)

A Model to Search for Synthesizable Molecules
John Bradshaw (University of Cambridge/MPI IS Tübingen) · Brooks Paige (Alan Turing Institute) · Matt J Kusner (University College London) · Marwin Segler (BenevolentAI) · José Miguel Hernández-Lobato (University of Cambridge)

Post training 4-bit quantization of convolutional networks for rapid-deployment
Ron Banner (Intel - Artificial Intelligence Products Group (AIPG)) · Yury Nahshan (Intel - Artificial Intelligence Products Group (AIPG)) · Daniel Soudry (Technion)

Fast and Flexible Multi-Task Classification using Conditional Neural Adaptive Processes
James Requeima (University of Cambridge / Invenia Labs) · Jonathan Gordon (University of Cambridge) · John Bronskill (University of Cambridge) · Sebastian Nowozin (Microsoft Research) · Richard Turner (Cambridge)

Differentially Private Anonymized Histograms
Ananda Theertha Suresh (Google)

Dynamic Local Regret for Non-convex Online Forecasting
Sergul Aydore (Stevens Institute of Technology) · Tianhao Zhu (Stevens Institute of Techonlogy) · Dean Foster (Amazon)

Learning Local Search Heuristics for Boolean Satisfiability
Emre Yolcu (Carnegie Mellon University) · Barnabas Poczos (Carnegie Mellon University)

Provably Efficient Q-Learning with Low Switching Cost
Yu Bai (Stanford University) · Tengyang Xie (University of Illinois at Urbana-Champaign) · Nan Jiang (University of Illinois at Urbana-Champaign) · Yu-Xiang Wang (UC Santa Barbara)

Solving graph compression via optimal transport
Vikas Garg (MIT) · Tommi Jaakkola (MIT)

PyTorch: An Imperative Style, High-Performance Deep Learning Library
Benoit Steiner (Facebook AI Research) · Zachary DeVito (Facebook AI Research) · Soumith Chintala (Facebook AI Research) · Sam Gross (Facebook) · Adam Paszke (University of Warsaw) · Francisco Massa (Facebook AI Research) · Adam Lerer (Facebook AI Research) · Gregory Chanan (Facebook) · Zeming Lin (Facebook AI Research) · Edward Yang (Facebook) · Alban Desmaison (Oxford University) · Alykhan Tejani (Twitter, Inc.) · Andreas Kopf (Xamla) · James Bradbury (Google Research) · Luca Antiga (Orobix) · Martin Raison (Nabla) · Natalia Gimelshein (NVIDIA) · Sasank Chilamkurthy (Qure.ai) · Trevor Killeen (Self Employed) · Lu Fang (Facebook) · Junjie Bai (Facebook)

Stability of Graph Scattering Transforms
Fernando Gama (University of Pennsylvania) · Alejandro Ribeiro (University of Pennsylvania) · Joan Bruna (NYU)

A Debiased MDI Feature Importance Measure for Random Forests
Xiao Li (University of California, Berkeley) · Yu Wang (UC Berkeley) · Sumanta Basu (Cornell University) · Karl Kumbier (University of California, Berkeley) · Bin Yu (UC Berkeley)

Difference Maximization Q-learning: Provably Efficient Q-learning with Function Approximation
Simon Du (Institute for Advanced Study) · Yuping Luo (Princeton University) · Ruosong Wang (Carnegie Mellon University) · Hanrui Zhang (Duke University)

Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models
Shanshan Wu (University of Texas at Austin) · Sujay Sanghavi (UT-Austin) · Alexandros Dimakis (University of Texas, Austin)

Fast Convergence of Natural Gradient Descent for Over-Parameterized Neural Networks
Guodong Zhang (University of Toronto) · James Martens (DeepMind) · Roger Grosse (University of Toronto)

Rapid Convergence of the Unadjusted Langevin Algorithm: Log-Sobolev Suffices
Santosh Vempala (Georgia Tech) · Andre Wibisono (Georgia Tech)

Learning Distributions Generated by One-Layer ReLU Networks
Shanshan Wu (University of Texas at Austin) · Alexandros Dimakis (University of Texas, Austin) · Sujay Sanghavi (UT-Austin)

Large-scale optimal transport map estimation using projection pursuit
Cheng Meng (University of Georgia) · Yuan Ke (University of Georgia) · Jingyi Zhang (The University of Georgia) · Mengrui Zhang (University of Georgia) · Wenxuan Zhong () · Ping Ma (University of Georgia)

A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement Learning
Nicolas Carion (Facebook AI Research Paris) · Nicolas Usunier (Facebook AI Research) · Gabriel Synnaeve (Facebook) · Alessandro Lazaric (Facebook Artificial Intelligence Research)

On Exact Computation with an Infinitely Wide Neural Net
Sanjeev Arora (Princeton University) · Simon Du (Institute for Advanced Study) · Wei Hu (Princeton University) · Zhiyuan Li (Princeton University) · Russ Salakhutdinov (Carnegie Mellon University) · Ruosong Wang (Carnegie Mellon University)

Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Gradient Estimators for Reinforcement Learning
Gregory Farquhar (University of Oxford) · Shimon Whiteson (University of Oxford) · Jakob Foerster (Facebook AI Research)

Chirality Nets for Human Pose Regression
Raymond Yeh (University of Illinois at Urbana–Champaign) · Yuan-Ting Hu (University of Illinois Urbana-Champaign) · Alexander Schwing (University of Illinois at Urbana-Champaign)

Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds
Minshuo Chen (Georgia Tech) · Haoming Jiang (Georgia Institute of Technology) · Wenjing Liao (Georgia Tech) · Tuo Zhao (Georgia Tech)

Fast Decomposable Submodular Function Minimization using Constrained Total Variation
Senanayak Sesh Kumar Karri (Imperial College London) · Francis Bach (INRIA - Ecole Normale Superieure) · Thomas Pock (Graz University of Technology)

Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model
Guodong Zhang (University of Toronto) · Lala Li (Google) · Zachary Nado (Google Inc.) · James Martens (DeepMind) · Sushant Sachdeva (University of Toronto) · George Dahl (Google Brain) · Chris Shallue (Google Brain) · Roger Grosse (University of Toronto)

Spherical Text Embedding
Yu Meng (University of Illinois at Urbana-Champaign) · Jiaxin Huang (University of Illinois Urbana-Champaign) · Guangyuan Wang (UIUC) · Chao Zhang (Georgia Institute of Technology) · Honglei Zhuang (Google Research) · Lance Kaplan (U.S. Army Research Laboratory) · Jiawei Han (UIUC)

Möbius Transformation for Fast Inner Product Search on Graph
Zhixin Zhou (Baidu Research) · Shulong Tan (Baidu Research) · Zhaozhuo Xu (Baidu Research) · Ping Li (Baidu Research USA)

Hyperbolic Graph Neural Networks
Qi Liu (University of Oxford) · Maximilian Nickel (Facebook AI Research) · Douwe Kiela (Facebook AI Research)

Average Individual Fairness: Algorithms, Generalization and Experiments
Saeed Sharifi-Malvajerdi (University of Pennsylvania) · Michael Kearns (University of Pennsylvania) · Aaron Roth (University of Pennsylvania)

Fixing the train-test resolution discrepancy
Hugo Touvron (Facebook AI Research) · Andrea Vedaldi (Facebook AI Research and University of Oxford) · Matthijs Douze (Facebook AI Research) · Herve Jegou (Facebook AI Research)

Modeling Dynamic Functional Connectivity with Latent Factor Gaussian Processes
Lingge Li (UC Irvine) · Dustin Pluta (UC Irvine) · Babak Shahbaba (UCI) · Norbert Fortin (UC Irvine) · Hernando Ombao (KAUST) · Pierre Baldi (UC Irvine)

Manipulating a Learning Defender and Ways to Counteract
Jiarui Gan (University of Oxford) · Qingyu Guo (Nanyang Technological University) · Long Tran-Thanh (University of Southampton) · Bo An (Nanyang Technological University) · Michael Wooldridge (Univ of Oxford)

Learning-In-The-Loop Optimization: End-To-End Control And Co-Design Of Soft Robots Through Learned Deep Latent Representations
Andrew Spielberg (Massachusetts Institute of Technology) · Allan Zhao (Massachusetts Institute of Technology) · Yuanming Hu (Massachusetts Institute of Technology) · Tao Du (MIT) · Wojciech Matusik (MIT) · Daniela Rus (Massachusetts Institute of Technology)

Learning to Infer Implicit Surfaces without 3D Supervision
Shichen Liu (Tsinghua University) · Shunsuke Saito (University of Southern California) · Weikai Chen (USC Institute for Creative Technology) · Hao Li (Pinscreen/University of Southern California/USC ICT)

Fast and Accurate Least-Mean-Squares Solvers
Ibrahim Jubran (The University of Haifa) · Alaa Maalouf (The University of Haifa) · Dan Feldman (University of Haifa)

Certifiable Robustness to Graph Perturbations
Aleksandar Bojchevski (Technical University of Munich) · Stephan Günnemann (Technical University of Munich)

Fast Convergence of Belief Propagation to Global Optima: Beyond Correlation Decay
Frederic Koehler (MIT)

Paradoxes in Fair Machine Learning
Paul Goelz (Carnegie Mellon University) · Anson Kahng (Carnegie Mellon University) · Ariel Procaccia (Carnegie Mellon University)

Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost
Zhuoran Yang (Princeton University) · Yongxin Chen (Georgia Institute of Technology) · Mingyi Hong (University of Minnesota) · Zhaoran Wang (Northwestern University)

The spiked matrix model with generative priors
Benjamin Aubin (Ipht Saclay) · Bruno Loureiro (IPhT Saclay) · Antoine Maillard (Ecole Normale Supérieure) · Florent Krzakala (ENS Paris & Sorbonnes Université) · Lenka Zdeborová (CEA Saclay)

Gradient Dynamics of Shallow Low-Dimensional ReLU Networks
Francis Williams (New York University) · Matthew Trager (NYU) · Daniele Panozzo (NYU) · Claudio Silva (New York University) · Denis Zorin (New York University) · Joan Bruna (NYU)

Robust and Communication-Efficient Collaborative Learning
Amirhossein Reisizadeh (UC Santa Barbara) · Hossein Taheri (UCSB) · Aryan Mokhtari (UT Austin) · Hamed Hassani (UPenn) · Ramtin Pedarsani (UC Santa Barbara)

Multiclass Learning from Contradictions
Sauptik Dhar (LG Electronics) · Vladimir Cherkassky (University of Minnesota) · Mohak Shah (LG Electronics)

Learning from Trajectories via Subgoal Discovery
Sujoy Paul (UC Riverside) · Jeroen Vanbaar (MERL (Mitsubishi Electric Research Laboratories), Cambridge MA) · Amit Roy-Chowdhury (University of California, Riverside, USA )

Distributed Low-rank Matrix Factorization With Exact Consensus
Zhihui Zhu (Johns Hopkins University) · Qiuwei Li (Colorado School of Mines) · Xinshuo Yang (Colorado School of Mines) · Gongguo Tang (Colorado School of Mines) · Michael B Wakin (Colorado School of Mines)

Online Normalization for Training Neural Networks
Vitaliy Chiley (Cerebras Systems) · Ilya Sharapov (Cerebras Systems) · Atli Kosson (Cerebras Systems) · Urs Koster (Cerebras Systems) · Ryan Reece (Cerebras Systems) · Sofia Samaniego de la Fuente (Cerebras Systems) · Vishal Subbiah (Cerebras Systems) · Michael James (Cerebras)

The Synthesis of XNOR Recurrent Neural Networks with Stochastic Logic
Arash Ardakani (McGill University) · Zhengyun Ji (McGill University) · Amir Ardakani (McGill University) · Warren Gross (McGill University)

An adaptive Mirror-Prox method for variational inequalities with singular operators
Kimon Antonakopoulos (Inria) · Veronica Belmega (ENSEA) · Panayotis Mertikopoulos (CNRS (French National Center for Scientific Research))

N-Gram Graph: A Simple Unsupervised Representation for Molecules
Shengchao Liu (UW-Madison) · Mehmet F Demirel (University of Wisconsin-Madison) · Yingyu Liang (University of Wisconsin Madison)

Characterizing the exact behaviors of temporal difference learning algorithms using Markov jump linear system theory
Bin Hu (University of Illinois at Urbana-Champaign) · Usman Syed (University of Illinois Urbana Champaign)

Facility Location Problem in Differential Privacy Model Revisited
Yunus Esencayi (State University of New York at Buffalo) · Marco Gaboardi (Univeristy at Buffalo) · Shi Li (University at Buffalo) · Di Wang (State University of New York at Buffalo)

Revisiting Auxiliary Latent Variables in Generative Models
John Lawson (Stanford University) · George Tucker (Google Brain) · Bo Dai (Google Brain) · Rajesh Ranganath (New York University)

Finite-time Analysis of Approximate Policy Iteration for the Linear Quadratic Regulator
Karl Krauth (UC berkeley) · Stephen Tu (UC Berkeley) · Benjamin Recht (UC Berkeley)

A Universally Optimal Multistage Accelerated Stochastic Gradient Method
Necdet Serhat Aybat (Penn State University) · Alireza Fallah (MIT) · Mert Gurbuzbalaban (Rutgers) · Asuman Ozdaglar (Massachusetts Institute of Technology)

From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction
Hidenori Tanaka (Stanford) · Aran Nayebi (Stanford University) · Stephen Baccus (Stanford University) · Surya Ganguli (Stanford)

Large Memory Layers with Product Keys
Guillaume Lample (Facebook AI Research) · Alexandre Sablayrolles (Facebook AI Research) · Marc'Aurelio Ranzato (Facebook AI Research) · Ludovic Denoyer (Facebook - FAIR) · Herve Jegou (Facebook AI Research)

Learning Deterministic Weighted Automata with Queries and Counterexamples
Gail Weiss (Technion) · Yoav Goldberg (Bar Ilan University) · Eran Yahav (Technion)

Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent
Jaehoon Lee (Google Brain) · Lechao Xiao (Google Brain) · Samuel Schoenholz (Google Brain) · Yasaman Bahri (Google Brain) · Roman Novak (Google Brain) · Jascha Sohl-Dickstein (Google Brain) · Jeffrey Pennington (Google Brain)

Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals
Surbhi Goel (The University of Texas at Austin) · Sushrut Karmalkar (The University of Texas at Austin) · Adam Klivans (UT Austin)

Visualizing and Measuring the Geometry of BERT
Emily Reif (Google) · Ann Yuan (Google) · Martin Wattenberg (Google) · Fernanda B Viegas (Google) · Andy Coenen (Google) · Adam Pearce (Google) · Been Kim (Google)

Self-Critical Reasoning for Robust Visual Question Answering
Jialin Wu (UT Austin) · Raymond Mooney (University of Texas at Austin)

Learning to Screen
Alon Cohen (Technion and Google Inc.) · Avinatan Hassidim (Google) · Haim Kaplan (TAU, GOOGLE) · Yishay Mansour (Tel Aviv University / Google) · Shay Moran (Google AI Princeton)

A Communication Efficient Stochastic Multi-Block Alternating Direction Method of Multipliers
Hao Yu (Alibaba Group (US) Inc )

A Little Is Enough: Circumventing Defenses For Distributed Learning
Gilad Baruch (Bar Ilan University) · Moran Baruch (Bar Ilan University) · Yoav Goldberg (Bar-Ilan University)

Error Correcting Output Codes Improve Probability Estimation and Adversarial Robustness of Deep Neural Networks
Gunjan Verma (ARL) · Ananthram Swami (Army Research Laboratory, Adelphi)

A Robust Non-Clairvoyant Dynamic Mechanism for Contextual Auctions
Yuan Deng (Duke University) · Sébastien Lahaie (Google Research) · Vahab Mirrokni (Google Research NYC)

Finite-Sample Analysis for SARSA with Linear Function Approximation
Shaofeng Zou (University at Buffalo, the State University of New York) · Tengyu Xu (The Ohio State University) · Yingbin Liang (The Ohio State University)

Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models
Stefano Sarao Mannelli (Institut de Physique Théorique) · Giulio Biroli (ENS) · Chiara Cammarota (King's College London) · Florent Krzakala (École Normale Supérieure) · Lenka Zdeborová (CEA Saclay)

Graph Structured Prediction Energy Networks
Colin Graber (University of Illinois at Urbana-Champaign) · Alexander Schwing (University of Illinois at Urbana-Champaign)

Private Learning Implies Online Learning: An Efficient Reduction
Alon Gonen (UCSD) · Elad Hazan (Princeton University) · Shay Moran (Google AI Princeton)

Graph Agreement Models for Semi-Supervised Learning
Otilia Stretcu (Carnegie Mellon University) · Krishnamurthy Viswanathan (Google Research) · Dana Movshovitz-Attias (Google) · Emmanouil Platanios (Carnegie Mellon University) · Sujith Ravi (Google Research) · Andrew Tomkins (Google)

Latent distance estimation for random geometric graphs
Ernesto Araya Valdivia (Université Paris-Sud) · Yohann De Castro (ENPC)

Seeing the Wind: Visual Wind Speed Prediction with a Coupled Convolutional and Recurrent Neural Network
Jennifer Cardona (Stanford University) · Michael Howland (Stanford University) · John Dabiri (Stanford University)

The Functional Neural Process
Christos Louizos (University of Amsterdam) · Xiahan Shi (Bosch Center for Artificial Intelligence) · Klamer Schutte (TNO) · Max Welling (University of Amsterdam / Qualcomm AI Research)

Recurrent Registration Neural Networks for Deformable Image Registration
Robin Sandkühler (Department of Biomedical Engineering, University of Basel) · Simon Andermatt (Center for medical Image Analysis and Navigation) · Grzegorz Bauman (University of Basel Hospital) · Sylvia Nyilas (Bern University Hospital) · Christoph Jud (University of Basel) · Philippe C. Cattin (University of Basel)

Unsupervised State Representation Learning in Atari
Ankesh Anand (Mila, Université de Montréal) · Evan Racah (Mila, Université de Montréal) · Sherjil Ozair (Université de Montréal) · Yoshua Bengio (Mila) · Marc-Alexandre Côté (Microsoft Research) · R Devon Hjelm (Microsoft Research)

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