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
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
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
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
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
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 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
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
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
pbSGD: Powered Stochastic Gradient Descent Methods for Accelerated Non-Convex Optimization Beitong Zhou, Jun Liu, Weigao Sun, Ruijuan Chen, Claire Tomlin, Ye Yuan
Positive Unlabeled Learning with Class-prior Approximation Shizhen Chang, Bo Du, Liangpei Zhang
Potential Driven Reinforcement Learning for Hard Exploration Tasks Enmin Zhao, Shihong Deng, Yifan Zang, Yongxin Kang, Kai Li, Junliang Xing
Privileged label enhancement with multi-label learning Wenfang Zhu, Xiuyi Jia, Weiwei Li
Quadratic Sparse Gaussian Graphical Model Estimation Method for Massive Variables Jiaqi Zhang, Meng Wang, Qinchi Li, Sen Wang, Xiaojun Chang, Beilun Wang
Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation Julian Berk, Sunil Gupta, Santu Rana, Svetha Venkatesh
RDF-to-Text Generation with Graph-augmented Structural Neural Encoders Hanning Gao, Lingfei Wu, Po Hu, Fangli Xu
Recurrent Dirichlet Belief Networks for interpretable Dynamic Relational Data Modelling Yaqiong Li, Xuhui Fan, Ling Chen, Bin Li, Zheng Yu, Scott A. Sisson
Reducing Underflow in Mixed Precision Training by Gradient Scaling Ruizhe Zhao, Brian Vogel, Tanvir Ahmed, Wayne Luk
Reinforcement Learning Framework for Deep Brain Stimulation Study Dmitrii Krylov, Remi Tachet des Combes, Romain Laroche, Michael Rosenblum, Dmitry V. Dylov
Reward Prediction Error as an Exploration Objective in Deep RL Riley Simmons-Edler, Ben Eisner, Daniel Yang, Anthony Bisulco, Eric Mitchell, Sebastian Seung, Daniel Lee
Scalable Gaussian Process Regression Networks Shibo Li, Wei Xing, Robert M. Kirby, Shandian Zhe
Self-adaptive Re-weighted Adversarial Domain Adaptation Shanshan Wang, Lei Zhang
Self-Attentional Credit Assignment for Transfer in Reinforcement Learning Johan Ferret, Raphael Marinier, Matthieu Geist, Olivier Pietquin
Self-paced Consensus Clustering with Bipartite Graph Peng Zhou, Liang Du, Xuejun Li
Semi-supervised Clustering via Pairwise Constrained Optimal Graph Feiping Nie, Han Zhang, Rong Wang, Xuelong Li
Seq-U-Net: A One-Dimensional Causal U-Net for Efficient Sequence Modelling Daniel Stoller, Mi Tian, Sebastian Ewert, Simon Dixon
Solving Hard AI Planning Instances Using Curriculum-Driven Deep Reinforcement Learning Dieqiao Feng, Carla Gomes, Bart Selman
Spectral Pruning: Compressing Deep Neural Networks via Spectral Analysis and its Generalization Error Taiji Suzuki, Hiroshi Abe, Tomoya Murata, Shingo Horiuchi, Kotaro Ito, Tokuma Wachi, So Hirai, Masatoshi Yukishima, Tomoaki Nishimura
Split to Be Slim: An Overlooked Redundancy in Vanilla Convolution Qiulin Zhang, Zhuqing Jiang, Qishuo Lu, Jia'nan Han, Zhengxin Zeng, Shanghua Gao, Aidong Men