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2020 IJCAI 接受论文 list 分类排列(二)_a dataset complexity measure for analogical transf

a dataset complexity measure for analogical transfer

2020 IJCAI 接受论文 list 分类排列(一)

2020 IJCAI 接受论文 list 分类排列(二)

2020 IJCAI 接受论文 list 分类排列(三)

目录

Main track (Humans and AI)

Main track (Knowledge Representation and Reasoning)

Main track (Machine Learning)

Main track (Machine Learning Applications)


 

Main track (Humans and AI)

  • Aggregating Crowd Wisdom with Side Information via a Clustering-based Label-aware Autoencoder
    Li'ang Yin, Yunfei Liu, Weinan Zhang, Yong Yu
  • Improving Knowledge Tracing via Pre-training Question Embeddings
    Yunfei Liu, Yang Yang, Xianyu Chen, Jian Shen, Haifeng Zhang, Yong Yu
  • Incorporating Failure Events in Agents’ Decision Making to Improve User Satisfaction
    Chen Rozenshtein, David Sarne
  • Learning Regional Attention Convolutional Neural Network for Motion Intention Recognition Based on EEG Data
    Zhijie Fang, Weiqun Wang, Shixin Ren, Jiaxing Wang, Weiguo Shi, Xu Liang, Chen-Chen Fan, Zeng-Guang Hou
  • Learning to complement humans
    Bryan Wilder, Eric Horvitz, Ece Kamar
  • LISNN: Improving Spiking Neural Networks with Lateral Interactions for Robust Object Recognition
    Xiang Cheng, Yunzhe Hao, Jiaming Xu, Bo Xu
  • Optimal Complex Task Assignment in Service Crowdsourcing
    Feilong Tang
  • Performance as a Constraint: An Improved Wisdom of Crowds Using Performance Regularization
    Jiyi Li, Yasushi Kawase, Yukino Baba, Hisashi Kashima
  • Structured Probabilistic End-to-End Learning from Crowds
    Zhijun Chen, Huimin Wang, Hailong Sun, Pengpeng Chen, Tao Han, Xudong Liu, Jie Yang

Main track (Knowledge Representation and Reasoning)

  • A Dataset Complexity Measure for Analogical Transfer
    Fadi Badra
  • A Framework for Reasoning about Dynamic Axioms in Description Logics
    Bartosz Bednarczyk, Stephane Demri, Alessio Mansutti
  • A Fully Rational Account of Structured Argumentation Under Resource Bounds
    Marcello D'Agostino, Sanjay Modgil
  • A Journey into Ontology Approximation: From Non-Horn to Horn
    Anneke Haga, Carsten Lutz, Johannes Marti, Frank Wolter
  • A Logic of Directions
    Heshan Du, Natasha Alechina, Anthony G. Cohn
  • A Modal Logic for Joint Abilities under Strategy Commitments
    Zhaoshuai Liu, Liping Xiong, Yongmei Liu, Yves Lespérance, Ronghai Xu, Hongyi Shi
  • Adversarial Oracular Seq2seq Learning for Sequential Recommendation
    Pengyu Zhao, Tianxiao Shui, Yuanxing Zhang, Kecheng Xiao, Kaigui Bian
  • All-Instances Oblivious Chase Termination is Undecidable for Single-Head Binary TGDs
    Bartosz Bednarczyk, Robert Ferens, Piotr Ostropolski-Nalewaja
  • Answering Counting Queries over DL-Lite Ontologies
    Meghyn Bienvenu, Quentin Manière, Michaël Thomazo
  • Automatic Synthesis of Generalized Winning Strategies of Impartial Combinatorial Games Using SMT Solvers
    Kaisheng Wu, Liangda Fang, Liping Xiong, Zhao-Rong Lai, Yong Qiao, Kaidong Chen, Fei Rong
  • Belief Merging Operators as Maximum Likelihood Estimators
    Patricia Everaere, Sebastien Konieczny, Pierre Marquis
  • Boolean Games: Inferring Agents' Goals Using Taxation Queries
    Abhijin Adiga, Sarit Kraus, Oleg Maksimov, S. S. Ravi
  • Concurrent Games in Dynamic Epistemic Logic
    Bastien Maubert, Sophie Pinchinat, Francois Schwarzentruber, Silvia Stranieri
  • Cone Semantics for Logics with Negation
    Özgür Lütfü Özçep, Mena Leemhuis, Diedrich Wolter
  • Controllability of Control Argumentation Frameworks
    Andreas Niskanen, Daniel Neugebauer, Matti Järvisalo
  • Controlled Query Evaluation in Description Logics Through Instance Indistinguishability
    Gianluca Cima, Domenico Lembo, Riccardo Rosati, Domenico Fabio Savo
  • Counting Query Answers over a DL-Lite KB
    Diego Calvanese, Julien Corman, Davide Lanti, Simon Razniewski
  • Deductive Module Extraction for Expressive Description Logics
    Patrick Koopmann, Jieying Chen
  • Deep Learning for Abstract Argumentation Semantics
    Dennis Craandijk, Floris Bex
  • Diagnosing Software Faults Using Multiverse Analysis
    Prantik Chatterjee, Abhijit Chatterjee, Jose Campos, Rui Abreu, Subhajit Roy
  • Enriching Documents with Compact, Representative, Relevant Knowledge Graphs
    Shuxin Li, Zixian Huang, Gong Cheng, Evgeny Kharlamov, Kalpa Gunaratna
  • Implementing Theory of Mind on a Robot Using Dynamic Epistemic Logic
    Lasse Dissing, Thomas Bolander
  • Inconsistency Measurement for Improving Logical Formula Clustering
    Yakoub Salhi
  • Lower Bounds and Faster Algorithms for Equality Constraints
    Peter Jonsson, Victor Lagerkvist
  • Lower Bounds for Approximate Knowledge Compilation
    Alexis de Colnet, Stefan Mengel
  • Maximizing the Spread of an Opinion in Few Steps: Opinion Diffusion in Non-Binary Networks
    Robert Bredereck, Lilian Jacobs, Leon Kellerhals
  • Model-Based Synthesis of Incremental and Correct Estimators for Discrete Event Systems
    Stéphanie Roussel, Xavier Pucel, Valentin Bouziat, Louise Travé-Massuyès
  • Model-theoretic Characterizations of Existential Rule Languages
    Heng Zhang, Yan Zhang, Guifei Jiang
  • Neural Entity Summarization with Joint Encoding and Weak Supervision
    Junyou Li, Gong Cheng, Qingxia Liu, Wen Zhang, Evgeny Kharlamov, Kalpa Gunaratna, Huajun Chen
  • NeurASP: Embracing Neural Networks into Answer Set Programming
    Zhun Yang, Adam Ishay, Joohyung Lee
  • On Computational Aspects of Iterated Belief Change
    Nicolas Schwind, Sebastien Konieczny, Jean-Marie Lagniez, Pierre Marquis
  • On Robustness in Qualitative Constraint Networks
    Michael Sioutis, Zhiguo Long, Tomi Janhunen
  • On the Decidability of Intuitionistic Tense Logic without Disjunction
    Fei Liang, Zhe Lin
  • On the Learnability of Possibilistic Theories
    Cosimo Persia, Ana Ozaki
  • Overcoming the Grounding Bottleneck Due to Constraints in ASP Solving: Constraints Become Propagators
    Bernardo Cuteri, Carmine Dodaro, Francesco Ricca, Peter Schüller
  • Pitfalls of Learning a Reward Function Online
    Stuart Armstrong, Jan Leike, Laurent Orseau, Shane Legg
  • Provenance for the Description Logic ELHr
    Camille Bourgaux, Ana Ozaki, Rafael Penaloza, Livia Predoiu
  • Query Answering for Existential Rules via Efficient Datalog Rewriting
    Zhe Wang, Peng Xiao, Kewen Wang, Zhiqiang Zhuang, Hai Wan
  • Ranking Semantics for Argumentation Systems With Necessities
    Dragan Doder, Srdjan Vesic, Madalina Croitoru
  • Reasoning Like Human: Hierarchical Reinforcement Learning for Knowledge Graph Reasoning
    Guojia Wan, Shirui Pan, Chen Gong, Chuan Zhou, Gholamreza Haffari
  • Revisiting the Notion of Extension over Incomplete Abstract Argumentation Frameworks
    Bettina Fazzinga, Sergio Flesca, Filippo Furfaro
  • Rewriting the Description Logic ALCHIQ to Disjunctive Existential Rules
    David Carral, Markus Krötzsch
  • Semantic Width and the Fixed-Parameter Tractability of Constraint Satisfaction Problems
    Hubie Chen, Georg Gottlob, Matthias Lanzinger, Reinhard Pichler
  • Smart Voting
    Rachael Colley, Umberto Grandi, Arianna Novaro
  • Solving Analogies on Words based on Minimal Complexity Transformation
    Pierre-Alexandre Murena, Marie Al-Ghossein, Jean-Louis Dessalles, Antoine Cornuéjols
  • Switch-List Representations in a Knowledge Compilation Map
    Ondřej Čepek, Miloš Chromý
  • Synthesizing strategies under expected and exceptional environment behaviors
    Benjamin Aminof, Giuseppe De Giacomo, Alessio Lomuscio, Aniello Murano, Sasha Rubin
  • The Complexity Landscape of Resource-Constrained Scheduling
    Robert Ganian, Thekla Hamm, Guillaume Mescoff
  • Threshold Treewidth and Hypertree Width
    Robert Ganian, Andre Schidler, Manuel Sorge, Stefan Szeider
  • Tractable Fragments of Datalog with Metric Temporal Operators
    Przemysław A. Wałęga, Bernardo Cuenca Grau, Mark Kaminski, Egor V. Kostylev

Main track (Machine Learning)

  • A Bi-level Formulation for Label Noise Learning with Spectral Cluster Discovery
    Yijing Luo, Bo Han, Chen Gong
  • A Dual Input-aware Factorization Machine for CTR Prediction
    Wantong Lu, Yantao Yu, Yongzhe Chang, Zhen Wang, Chenhui Li, Bo Yuan
  • A Graphical and Attentional Framework for Dual-Target Cross-Domain Recommendation
    Feng Zhu, Yan Wang, Chaochao Chen, Guanfeng Liu, Xiaolin Zheng
  • A new attention mechanism to classify multivariate time series
    Yifan Hao, Huiping Cao
  • Accelerating Stratified Sampling SGD by Reconstructing Strata
    Weijie Liu, Hui Qian, Chao Zhang, Zebang Shen, Jiahao Xie, Nenggan Zheng
  • AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search
    Daoyuan Chen, Yaliang Li, Minghui Qiu, Zhen Wang, Bofang Li, Bolin Ding, Hongbo Deng, Jun Huang, Wei Lin, Jingren Zhou
  • Adaptively Multi-Objective Adversarial Training for Dialogue Generation
    Xuemiao Zhang, Zhouxing Tan, Xiaoning Zhang, Yang Cao, Rui Yan
  • An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles
    Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani
  • Analysis of Q-learning with Adaptation and Momentum Restart for Gradient Descent
    Bowen Weng, Huaqing Xiong, Yingbin Liang, Wei Zhang
  • Arbitrary Talking Face Generation via Attentional Audio-Visual Coherence Learning
    Hao Zhu, Huaibo Huang, Yi Li, Aihua Zheng, Ran He
  • Argot: Generating Adversarial Readable Chinese Texts
    Zihan Zhang, Mingxuan Liu, Chao Zhang, Yiming Zhang, Zhou Li, Qi Li, Haixin Duan, Donghong Sun
  • Asymmetric Distribution Measure for Few-shot Learning
    Wenbin Li, Lei Wang, Jing Huo, Yinghuan Shi, Yang Gao, Jiebo Luo
  • BaKer-Nets: Bayesian Random Kernel Mapping Networks
    Hui Xue, Zheng-Fan Wu
  • Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning
    Ishan Durugkar, Elad Liebman, Peter Stone
  • Batch Decorrelation for Active Metric Learning
    Priyadarshini Kumari, Ritesh Goru, Siddhartha Chaudhuri, Subhasis Chaudhuri
  • Bayesian Decision Process for Budget-efficient Crowdsourced Clustering
    Xiaozhou Wang, Xi Chen, Qihang Lin, Weidong Liu
  • Bayesian Optimization using Pseudo-Points
    Chao Qian, Hang Xiong, Ke Xue
  • BERT-INT:A BERT-based Interaction Model For Knowledge Graph Alignment
    Xiaobin Tang, Jing Zhang, Bo Chen, Yang Yang, Hong Chen, Cuiping Li
  • Best Arm Identification in Spectral Bandits
    Tomáš Kocák, Aurélien Garivier
  • Beyond Network Pruning: a Joint Search-and-Training Approach
    Xiaotong Lu, Han Huang, Weisheng Dong, Xin Li, Guangming Shi
  • BRPO: Batch Residual Policy Optimization
    Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed Chi, Craig Boutilier
  • Can Cross Entropy Loss Be Robust to Label Noise?
    Lei Feng, Senlin Shu, Zhuoyi Lin, Fengmao Lv, Li Li, Bo An
  • CDIMC-net: Cognitive Deep Incomplete Multi-view Clustering Network
    Jie Wen, Zheng Zhang, Yong Xu, Bob Zhang, Lunke Fei, Guo-Sen Xie
  • Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation
    Yiyang Zhang, Feng Liu, Zhen Fang, Bo Yuan, Guangquan Zhang, Jie Lu
  • Class Prior Estimation in Active Positive and Unlabeled Learning
    Lorenzo Perini, Vincent Vercruyssen, Jesse Davis
  • Classification with Rejection: Scaling Generative Classifiers with Supervised Deep Infomax
    Xin Wang, Siu Ming Yiu
  • Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks
    Jinghui Chen, Dongruo Zhou, Yiqi Tang, Ziyan Yang, Yuan Cao, Quanquan Gu
  • Collaboration Based Multi-Label Propagation for Fraud Detection
    Haobo Wang, Zhao Li, Jiaming Huang, Pengrui Hui, Weiwei Liu, Tianlei Hu, Gang Chen
  • Collaborative Self-Attention Network for Session-based Recommendation
    Anjing Luo, Pengpeng Zhao, Yanchi Liu, Fuzhen Zhuang, Deqing Wang, Jiajie Xu, Junhua Fang, Victor S. Sheng
  • Coloring Graph Neural Networks for Node Disambiguation
    George Dasoulas, Ludovic Dos Santos, Kevin Scaman, Aladin Virmaux
  • Combinatorial Multi-Armed Bandits with Concave Rewards and Fairness Constraints
    Huanle Xu, Yang Liu, Wing Cheong Lau, Rui Li
  • Communicative Representation Learning on Attributed Molecular Graphs
    Ying Song, Shuangjia Zheng, Zhangming Niu, Zhang-hua Fu, Yutong Lu, Yuedong Yang
  • Complete Bottom-Up Predicate Invention in Meta-Interpretive Learning
    Céline Hocquette, Stephen H. Muggleton
  • Compressed Self-Attention for Deep Metric Learning with Low-Rank Approximation
    Ziye Chen, Mingming Gong, Lingjuan Ge, Bo Du
  • Consistent MetaReg: Alleviating Intra-task Discrepancy for Better Meta-knowledge
    Pinzhuo Tian, Lei Qi, Shaokang Dong, Yinghuan Shi, Yang Gao
  • Constrained Policy Improvement for Efficient Reinforcement Learning
    Elad Sarafian, Aviv Tamar, Sarit Kraus
  • Contextualized Point-of-Interest Recommendation
    Peng Han, Zhongxiao Li, Yong Liu, Peilin Zhao, Jing Li, Hao Wang, Shuo Shang
  • Convolutional Neural Networks with Compression Complexity Pooling for Out-of-Distribution Image Detection
    Sehun Yu, Dongha Lee, Hwanjo Yu
  • Crowdsourcing with Multiple-Source Knowledge Transfer
    Guangyang Han, Jinzheng Tu, Guoxian Yu, Jun Wang, Carlotta Domeniconi
  • DACE: Distribution-Aware Counterfactual Explanation by Mixed-Integer Linear Optimization
    Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Hiroki Arimura
  • Decorrelated Clustering with Data Selection Bias
    Xiao Wang, Shaohua Fan, Kun Kuang, Chuan Shi, Jiawei Liu, Bai Wang
  • Deep Feedback Network for Recommendation
    Ruobing Xie, Cheng Ling, Yalong Wang, Rui Wang, Feng Xia, Leyu Lin
  • Deep Latent Low-Rank Fusion Network for Progressive Subspace Discovery
    Zhao Zhang, Jiahuan Ren, Zheng Zhang, Guangcan Liu
  • DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction
    Alexander Schulz, Fabian Hinder, Barbara Hammer
  • Diffusion Variational Autoencoders
    Luis A. Perez Rey, Vlado Menkovski, Jim Portegies
  • Direct Quantization for Training Highly Accurate Low Bit-width Deep Neural Networks
    Tuan Hoang, Thanh-Toan Do, Tam V. Nguyen, Ngai-Man Cheung
  • Discovering Latent Class Labels for Multi-Label Learning
    Jun Huang, Linchuan Xu, Jing Wang, Lei Feng, Kenji Yamanishi
  • Discovering Subsequence Patterns for Next POI Recommendation
    Kangzhi Zhao, Yong Zhang, Hongzhi Yin, Jin Wang, Kai Zheng, Xiaofang Zhou, Chunxiao Xing
  • Discriminative Feature Selection via A Structured Sparse Subspace Learning Module
    Zheng Wang, Feiping Nie, Lai Tian, Rong Wang, Xuelong Li
  • Disentangling Direct and Indirect Interactions in Polytomous Item Response Theory Models
    Frank Nussbaum, Joachim Giesen
  • DropNAS: Grouped Operation Dropout for Differentiable Architecture Search
    Weijun Hong, Guilin Li, Weinan Zhang, Ruiming Tang, Yunhe Wang, Zhenguo Li, Yong Yu
  • Dual Policy Distillation
    Kwei-Herng Lai, Daochen Zha, Yuening Li, Xia Hu
  • Effective Search of Logical Forms for Weakly Supervised Knowledge-Based Question Answering
    Tao Shen, Xiubo Geng, Guodong Long, Jing Jiang, Chengqi Zhang, Daxin Jiang
  • Efficient Deep Reinforcement Learning via Adaptive Policy Transfer
    Tianpei Yang, Jianye Hao, Zhaopeng Meng, Zongzhang Zhang, Yujing Hu, Yingfeng Chen, Changjie Fan, Weixun Wang, Wulong Liu, Zhaodong Wang, Jiajie Peng
  • Embodied Multimodal Multitask Learning
    Devendra Singh Chaplot, Lisa Lee, Ruslan Salakhutdinov, Devi Parikh, Dhruv Batra
  • EndCold: An End-to-End Framework for Cold Question Routing in Community Question Answering Services
    Jiankai Sun, Jie Zhao, Huan Sun, Srinivasan Parthasarathy
  • Evaluating and Aggregating Feature-based Model Explanations
    Umang Bhatt, Adrian Weller, José M. F. Moura
  • Explainable Inference on Sequential Data via Memory-Tracking
    Biagio La Rosa, Roberto Capobianco, Daniele Nardi
  • Explainable Recommendation via Interpretable Feature Mapping and Evaluation of Explainability
    Deng Pan, Xiangrui Li, Xin Li, Dongxiao Zhu
  • Exploiting Neuron and Synapse Filter Dynamics in Spatial Temporal Learning of Deep Spiking Neural Network
    Haowen Fang, Amar Shrestha, Ziyi Zhao, Qinru Qiu
  • Exploring Parameter Space with Structured Noise for Meta-Reinforcement Learning
    Hui Xu, Chong Zhang, Jiaxing Wang, Deqiang Ouyang, Yu Zheng, Jie Shao
  • Fairness-Aware Neural Rényi Minimization for Continuous Features
    Vincent Grari, Sylvain Lamprier, Marcin Detyniecki
  • Feature Statistics Guided Efficient Filter Pruning
    Hang Li, Chen Ma, Wei Xu, Xue Liu
  • Flow-based Intrinsic Curiosity Module
    Hsuan-Kung Yang, Po-Han Chiang, Min-Fong Hong, Chun-Yi Lee
  • FNNC: Achieving Fairness through Neural Networks
    Manisha Padala, Sujit Gujar
  • Fully Nested Neural Network for Adaptive Compression and Quantization
    Yufei Cui, Ziquan Liu, Wuguannan Yao, Qiao Li, Antoni B. Chan, Tei-wei Kuo, Chun Jason Xue
  • General Purpose MRF Learning with Neural Network Potentials
    Hao Xiong, Nicholas Ruozzi
  • Generalized Mean Estimation in Monte-Carlo Tree Search
    Tuan Dam, Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen
  • Generating Robust Audio Adversarial Examples with Temporal Dependency
    Hongting Zhang, Pan Zhou, Qiben Yan, Xiao-Yang Liu
  • Gradient Perturbation is Underrated for Differentially Private Convex Optimization
    Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
  • Greedy Convex Ensemble
    Thanh Tan Nguyen, Nan Ye, Peter Bartlett
  • Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks
    Maxime Wabartha, Audrey Durand, Vincent François-Lavet, Joelle Pineau
  • Human-Driven FOL Explanations of Deep Learning
    Gabriele Ciravegna, Francesco Giannini, Marco Gori, Marco Maggini, Stefano Melacci
  • Hybrid Learning for Multi-agent Cooperation with Sub-optimal Demonstrations
    Peixi Peng, Junliang Xing, Lili Cao
  • Hypothesis Sketching for Online Kernel Selection in Continuous Kernel Space
    Xiao Zhang, Shizhong Liao
  • I²HRL: Interactive Influence-based Hierarchical Reinforcement Learning
    Rundong Wang, Runsheng Yu, Bo An, Zinovi Rabinovich
  • I4R: Promoting Deep Reinforcement Learning by the Indicator for Expressive Representations
    Xufang Luo, Qi Meng, Di He, Wei Chen, Yunhong Wang
  • Independent Skill Transfer for Deep Reinforcement Learning
    Qiangxing Tian, Guanchu Wang, Jinxin Liu, Donglin Wang, Yachen Kang
  • Inference-Masked Loss for Deep Structured Output Learning
    Quan Guo, Hossein Rajaby Faghihi, Yue Zhang, Andrzej Uszok, Parisa Kordjamshidi
  • Intent Preference Decoupling for User Representation on Online Recommender System
    Zhaoyang Liu, Haokun Chen, Fei Sun, Xu Xie, Jinyang Gao, Bolin Ding, Yanyan Shen
  • Intention2Basket: A Neural Intention-driven Approach for Dynamic Next-basket Planning
    Shoujin Wang, Liang Hu, Yan Wang, Quan Z. Sheng, Mehmet Orgun, Longbing Cao
  • Internal and Contextual Attention Network for Cold-start Multi-channel Matching in Recommendation
    Ruobing Xie, Zhijie Qiu, Jun Rao, Yi Liu, Bo Zhang, Leyu Lin
  • Interpretable Models for Understanding Immersive Simulations
    Nicholas Hoernle, Kobi Gal, Barbara Grosz, Leilah Lyons, Ada Ren, Andee Rubin
  • IR-VIC: Unsupervised Discovery of Sub-goals for Transfer in RL
    Nirbhay Modhe, Prithvijit Chattopadhyay, Mohit Sharma, Abhishek Das, Devi Parikh, Dhruv Batra, Ramakrishna Vedantam
  • Is the Skip Connection Provable to Reform the Neural Network Loss Landscape?
    Lifu Wang, Bo Shen, Ning Zhao, Zhiyuan Zhang
  • Joint Multi-view 2D Convolutional Neural Networks for 3D Object Classification
    Jinglin Xu, Xiangsen Zhang, Wenbin Li, Xinwang Liu, Junwei Han
  • Joint Partial Optimal Transport for Open Set Domain Adaptation
    Renjun Xu, Pelen Liu, Yin Zhang, Fang Cai, Jindong Wang, Shuoying Liang, Heting Ying, Jianwei Yin
  • KGNN: Knowledge Graph Neural Network for Drug-Drug Interaction Prediction
    Xuan Lin, Zhe Quan, Zhi-Jie Wang, Tengfei Ma, Xiangxiang Zeng
  • Knowledge Hypergraphs: Prediction Beyond Binary Relations
    Bahare Fatemi, Perouz Taslakian, David Vazquez, David Poole
  • Knowledge-Based Regularization in Generative Modeling
    Naoya Takeishi, Yoshinobu Kawahara
  • KoGuN: Accelerating Deep Reinforcement Learning via Integrating Human Suboptimal Knowledge
    Peng Zhang, Jianye Hao, Weixun Wang, Hongyao Tang, Yi Ma, Yihai Duan, Yan Zheng
  • Label Distribution for Learning with Noisy Labels
    Yun-Peng Liu, Ning Xu, Yu Zhang, Xin Geng
  • Label Enhancement for Label Distribution Learning via Prior Knowledge
    Yongbiao Gao, Yu Zhang, Xin Geng
  • Learning and Solving Regular Decision Processes
    Eden Abadi, Ronen I. Brafman
  • Learning from Few Positives: a Provably Accurate Metric Learning Algorithm to Deal with Imbalanced Data
    Rémi Viola, Rémi Emonet, Amaury Habrard, Guillaume Metzler, Marc Sebban
  • Learning From Multi-Dimensional Partial Labels
    Haobo Wang, Weiwei Liu, Yang Zhao, Tianlei Hu, Ke Chen, Gang Chen
  • Learning in the Wild with Incremental Skeptical Gaussian Processes
    Andrea Bontempelli, Stefano Teso, Fausto Giunchiglia, Andrea Passerini
  • Learning Interpretable Models in the Property Specification Language
    Rajarshi Roy, Dana Fisman, Daniel Neider
  • Learning Interpretable Representations with Informative Entanglements
    Ege Beyazıt, Doruk Tuncel, Xu Yuan, Nian-Feng Tzeng, Xindong Wu
  • Learning Large Logic Programs By Going Beyond Entailment
    Andrew Cropper, Sebastijan Dumančic
  • Learning Neural-Symbolic Descriptive Planning Models via Cube-Space Priors: The Voyage Home (to STRIPS)
    Masataro Asai, Christian Muise
  • Learning Personalized Itemset Mapping for Cross-Domain Recommendation
    Yinan Zhang, Yong Liu, Peng Han, Chunyan Miao, Lizhen Cui, Baoli Li, Haihong Tang
  • Learning with Labeled and Unlabeled Multi-Step Transition Data for Recovering Markov Chain from Incomplete Transition Data
    Masahiro Kohjima, Takeshi Kurashima, Hiroyuki Toda
  • Learning With Subquadratic Regularization : A Primal-Dual Approach
    Raman Sankaran, Francis Bach, Chiranjib Bhattacharyya
  • Location Prediction over Sparse User Mobility Traces Using RNNs: Flashback in Hidden States!
    Dingqi Yang, Benjamin Fankhauser, Paolo Rosso, Philippe Cudre-Mauroux
  • Logic Constrained Pointer Networks for Interpretable Textual Similarity
    Subhadeep Maji, Rohan Kumar, Manish Bansal, Kalyani Roy, Pawan Goyal
  • LSGCN: Long Short-Term Traffic Prediction with Graph Convolutional Networks
    Rongzhou Huang, Chuyin Huang, Yubao Liu, Genan Dai, Weiyang Kong
  • MaCAR: Urban Traffic Light Control via Active Multi-agent Communication and Action Rectification
    Zhengxu Yu, Shuxian Liang, Long Wei, Zhongming Jin, Jianqiang Huang, Deng Cai, Xiaofei He, Xian-Sheng Hua
  • Marthe: Scheduling the Learning Rate Via Online Hypergradients
    Michele Donini, Luca Franceschi, Orchid Majumder, Massimiliano Pontil, Paolo Frasconi
  • Measuring the Discrepancy between Conditional Distributions: Methods, Properties and Applications
    Shujian Yu, Ammar Shaker, Francesco Alesiani, Jose Principe
  • Memory Augmented Neural Model for Incremental Session-based Recommendation
    Fei Mi, Boi Faltings
  • MergeNAS: Merge Operations into One for Differentiable Architecture Search
    Xiaoxing Wang, Chao Xue, Junchi Yan, Xiaokang Yang, Yonggang Hu, Kewei Sun
  • Metric Learning in Optimal Transport for Domain Adaptation
    Tanguy Kerdoncuff, Rémi Emonet, Marc Sebban
  • Mixed-Variable Bayesian Optimization
    Erik Daxberger, Anastasia Makarova, Matteo Turchetta, Andreas Krause
  • Multi-Class Imbalanced Graph Convolutional Network Learning
    Min Shi, Yufei Tang, Xingquan Zhu, David Wilson, Jianxun Liu
  • Multi-Feedback Bandit Learning with Probabilistic Contexts
    Luting Yang, Jianyi Yang, Shaolei Ren
  • Multi-label Feature Selection via Global Relevance and Redundancy Optimization
    Jia Zhang, Yidong Lin, Min Jiang, Shaozi Li, Yong Tang, Kay Chen Tan
  • Multi-Scale Group Transformer for Long Sequence Modeling in Speech Separation
    Yucheng Zhao, Chong Luo, Zheng-Jun Zha, Wenjun Zeng
  • Multi-View Attribute Graph Convolution Networks for Clustering
    Jiafeng Cheng, Qianqian Wang, Zhiqiang Tao, Deyan Xie, Quanxue Gao
  • MULTIPOLAR: Multi-Source Policy Aggregation for Transfer Reinforcement Learning between Diverse Environmental Dynamics
    Mohammadamin Barekatain, Ryo Yonetani, Masashi Hamaya
  • Multivariate Probability Calibration with Isotonic Bernstein Polynomials
    Yongqiao Wang, Xudong Liu
  • Mutual Information Estimation using LSH Sampling
    Ryan Spring, Anshumali Shrivastava
  • Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs
    Bo Xue, Guanghui Wang, Yimu Wang, Lijun Zhang
  • Neighbor Combinatorial Attention for Critical Structure Mining
    Tanli Zuo, Yukun Qiu, Wei-Shi Zheng
  • Neural Representation and Learning of Hierarchical 2-additive Choquet Integrals
    Roman Bresson, Johanne Cohen, Eyke Hüllermeier, Christophe Labreuche, Michèle Sebag
  • Neural Tensor Model for Learning Multi-Aspect Factors in Recommender Systems
    Huiyuan Chen, Jing Li
  • Non-monotone DR-submodular Maximization over General Convex Sets
    Christoph Dürr, Nguyen Kim Thang, Abhinav Srivastav, Léo Tible
  • On Deep Unsupervised Active Learning
    Changsheng Li, Handong Ma, Zhao Kang, Ye Yuan, Xiao-Yu Zhang, Guoren Wang
  • On Metric DBSCAN with Low Doubling Dimension
    Hu Ding, Fan Yang, Mingyue Wang
  • One-Shot Neural Architecture Search via Novelty Driven Sampling
    Miao Zhang, Huiqi Li, Shirui Pan, Taoping Liu, Steven Su
  • Online Positive and Unlabeled Learning
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Main track (Machine Learning Applications)

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