2020 IJCAI 接受论文 list 分类排列（二）
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
Chuang Zhang, Chen Gong, Tengfei Liu, Xun Lu, Weiqiang Wang, Jian Yang - Only Relevant Information Matters: Filtering Out Noisy Samples To Boost RL
Yannis Flet-Berliac, Philippe Preux - Optimal Margin Distribution Machine for Multi-Instance Learning
Teng Zhang, Hai Jin - Optimality, Accuracy, and Efficiency of an Exact Functional Test
Hien H. Nguyen, Hua Zhong, Mingzhou Song - Order-Dependent Event Models for Agent Interactions
Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian - P-KDGAN: Progressive Knowledge Distillation with GANs for One-class Novelty Detection
Zhiwei Zhang, Shifeng Chen, Lei Sun - Partial Multi-Label Learning via Multi-Subspace Representation
Ziwei Li, Gengyu Lyu, Songhe Feng - 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 - Reinforcement Learning with Dynamic Boltzmann Softmax Updates
Ling Pan, Qingpeng Cai, Qi Meng, Wei Chen, Longbo Huang - 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 - SI-VDNAS: Semi-Implicit Variational Dropout for Hierarchical One-shot Neural Architecture Search
Yaoming Wang, Wenrui Dai, Chenglin Li, Junni Zou, Hongkai Xiong - Sinkhorn Regression
Lei Luo, Jian Pei, Heng Huang - Smart Contract Vulnerability Detection using Graph Neural Network
Yuan Zhuang, Zhenguang Liu, Peng Qian, Qi Liu, Xiang Wang, Qinming He - Soft Threshold Ternary Networks
Weixiang Xu, Xiangyu He, Tianli Zhao, Qinghao Hu, Peisong Wang, Jian Cheng - 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 - Stabilizing Adversarial Invariance Induction from Divergence Minimization Perspective
Yusuke Iwasawa, Kei Akuzawa, Yutaka Matsuo - Stochastic Batch Augmentation with An Effective Distilled Dynamic Soft Label Regularizer
Qian Li, Qingyuan Hu, Yong Qi, Saiyu Qi, Jie Ma, Jian Zhang - SVRG for Policy Evaluation with Fewer Gradient Evaluations
Zilun Peng, Ahmed Touati, Pascal Vincent, Doina Precup - Switching Poisson Gamma Dynamical Systems
Wenchao Chen, Bo Chen, Yicheng Liu, Qianru Zhao, Mingyuan Zhou - Synthesizing Aspect-Driven Recommendation Explanations from Reviews
Trung-Hoang Le, Hady W. Lauw - Temporal Attribute Prediction via Joint Modeling of Multi-Relational Structure Evolution
Sankalp Garg, Navodita Sharma, Woojeong Jin, Xiang Ren - Tensor-based multi-view label enhancement for multi-label learning
Fangwen Zhang, Xiuyi Jia, Weiwei Li - Textual Membership Queries
Jonathan Zarecki, Shaul Markovitch - The Importance of the Test Set Size in Quantification Assessment
André Maletzke, Waqar Hassan, Denis dos Reis, Gustavo Batista - The Sparse MinMax k-Means Algorithm for High-Dimensional Clustering
Sayak Dey, Swagatam Das, Rammohan Mallipeddi - Tight Convergence Rate of Gradient Descent for Eigenvalue Computation
Qinghua Ding, Kaiwen Zhou, James Cheng - Toward a neuro-inspired creative decoder
Payel Das, Brian Quanz, Pin-Yu Chen, Jae-wook Ahn, Dhruv Shah - Towards a Hierarchical Bayesian Model of Multi-View Anomaly Detection
Zhen Wang, Chao Lan - Towards Accurate and Robust Domain Adaptation under Noisy Environments
Zhongyi Han, Xian-Jin Gui, Chaoran Cui, Yilong Yin - Towards Explainable Conversational Recommendation
Zhongxia Chen, Xiting Wang, Xing Xie, Mehul Parsana, Akshay Soni, Xiang Ao, Enhong Chen - Trajectory Similarity Learning with Auxiliary Supervision and Optimal Matching
Hanyuan Zhang, Xinyu Zhang, Qize Jiang, Baihua Zheng, Zhenbang Sun, Weiwei Sun, Changhu Wang - TransRHS: A Representation Learning Method for Knowledge Graphs with Relation Hierarchical Structure
Fuxiang Zhang, Xin Wang, Zhao Li, Jianxin Li - Triple-GAIL: A Multi-Modal Imitation Learning Framework with Generative Adversarial Nets
Cong Fei, Bin Wang, Yuzheng Zhuang, Zongzhang Zhang, Jianye Hao, Hongbo Zhang, Xuewu Ji, Wulong Liu - Understanding the Power and Limitations of Teaching with Imperfect Knowledge
Rati Devidze, Farnam Mansouri, Luis Haug, Yuxin Chen, Adish Singla - Unsupervised Domain Adaptation with Dual-Scheme Fusion Network for Medical Image Segmentation
Danbing Zou, Qikui Zhu, Pingkun Yan - Unsupervised Monocular Visual-inertial Odometry Network
Peng Wei, Guoliang Hua, Weibo Huang, Fanyang Meng, Hong Liu - Unsupervised Representation Learning by Predicting Random Distances
Hu Wang, Guansong Pang, Chunhua Shen, Congbo Ma - User Modeling with Click Preference and Reading Satisfaction for News Recommendation
Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang - Variational Learning of Bayesian Neural Networks via Bayesian Dark Knowledge
Gehui Shen, Xi Chen, Zhihong Deng - Weakly-Supervised Multi-view Multi-instance Multi-label Learning
Yuying Xing, Guoxian Yu, Jun Wang, Carlotta Domeniconi, Xiangliang Zhang