IJCAI 2020

778 papers

Internal and Contextual Attention Network for Cold-start Multi-channel Matching in Recommendation

Ruobing Xie, Zhijie Qiu, Jun Rao, Yi Liu, Bo Zhang

Accelerating Stratified Sampling SGD by Reconstructing Strata

Weijie Liu, Hui Qian, Chao Zhang, Zebang Shen, Jiahao Xie

Consistent MetaReg: Alleviating Intra-task Discrepancy for Better Meta-knowledge

Pinzhuo Tian, Lei Qi, Shaokang Dong, Yinghuan Shi, Yang Gao

Only Relevant Information Matters: Filtering Out Noisy Samples To Boost RL

Yannis Flet-Berliac, Philippe Preux

Diffusion Variational Autoencoders

Luis A. Perez Rey, Vlado Menkovski, Jim Portegies

SVRG for Policy Evaluation with Fewer Gradient Evaluations

Zilun Peng, Ahmed Touati, Pascal Vincent, Doina Precup

Explainable Recommendation via Interpretable Feature Mapping and Evaluation of Explainability

Deng Pan, Xiangrui Li, Xin Li, Dongxiao Zhu

Optimality, Accuracy, and Eﬀiciency of an Exact Functional Test

Hien H. Nguyen, Hua Zhong, Mingzhou Song

Learning Neural-Symbolic Descriptive Planning Models via Cube-Space Priors: The Voyage Home (to STRIPS)

Masataro Asai, Christian Muise

I4R: Promoting Deep Reinforcement Learning by the Indicator for Expressive Representations

Xufang Luo, Qi Meng, Di He, Wei Chen, Yunhong Wang

Textual Membership Queries

Jonathan Zarecki, Shaul Markovitch

Self-Attentional Credit Assignment for Transfer in Reinforcement Learning

Johan Ferret, Raphael Marinier, Matthieu Geist, Olivier Pietquin

Understanding the Power and Limitations of Teaching with Imperfect Knowledge

Rati Devidze, Farnam Mansouri, Luis Haug, Yuxin Chen, Adish Singla

The Importance of the Test Set Size in Quantification Assessment

André Maletzke, Waqar Hassan, Denis dos Reis, Gustavo Batista

Mixed-Variable Bayesian Optimization

Erik Daxberger, Anastasia Makarova, Matteo Turchetta, Andreas Krause

On Deep Unsupervised Active Learning

Changsheng Li, Handong Ma, Zhao Kang, Ye Yuan, Xiao-Yu Zhang

Feature Statistics Guided Efficient Filter Pruning

Hang Li, Chen Ma, Wei Xu, Xue Liu

Partial Multi-Label Learning via Multi-Subspace Representation

Ziwei Li, Gengyu Lyu, Songhe Feng

A Bi-level Formulation for Label Noise Learning with Spectral Cluster Discovery

Yijing Luo, Bo Han, Chen Gong

Sinkhorn Regression

Lei Luo, Jian Pei, Heng Huang

Collaborative Self-Attention Network for Session-based Recommendation

Anjing Luo, Pengpeng Zhao, Yanchi Liu, Fuzhen Zhuang, Deqing Wang

Beyond Network Pruning: a Joint Search-and-Training Approach

Xiaotong Lu, Han Huang, Weisheng Dong, Xin Li, GUANGMING Shi

Intent Preference Decoupling for User Representation on Online Recommender System

Zhaoyang Liu, Haokun Chen, Fei Sun, Xu Xie, Jinyang Gao

Label Distribution for Learning with Noisy Labels

Yun-Peng Liu, Ning Xu, Yu Zhang, Xin Geng

Learning Personalized Itemset Mapping for Cross-Domain Recommendation

Yinan Zhang, Yong Liu, Peng Han, Chunyan Miao, Lizhen Cui

Combinatorial Multi-Armed Bandits with Concave Rewards and Fairness Constraints

Huanle Xu, Yang Liu, Wing Cheong Lau, Rui Li

Multivariate Probability Calibration with Isotonic Bernstein Polynomials

Yongqiao Wang, Xudong Liu

Joint Partial Optimal Transport for Open Set Domain Adaptation

Renjun Xu, Pelen Liu, Yin Zhang, Fang Cai, Jindong Wang

Argot: Generating Adversarial Readable Chinese Texts

Zihan Zhang, Mingxuan Liu, Chao Zhang, Yiming Zhang, Zhou Li

Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation

Yiyang Zhang, Feng Liu, Zhen Fang, Bo Yuan, Guangquan Zhang

Deep Feedback Network for Recommendation

Ruobing Xie, Cheng Ling, Yalong Wang, Rui Wang, Feng Xia

Multi-label Feature Selection via Global Relevance and Redundancy Optimization

Jia Zhang, Yidong Lin, Min Jiang, Shaozi Li, Yong Tang

Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning

Ishan Durugkar, Elad Liebman, Peter Stone

Hypothesis Sketching for Online Kernel Selection in Continuous Kernel Space

Xiao Zhang, Shizhong Liao

MaCAR: Urban Traffic Light Control via Active Multi-agent Communication and Action Rectification

Zhengxu Yu, Shuxian Liang, Long Wei, Zhongming Jin, Jianqiang Huang

Contextualized Point-of-Interest Recommendation

Peng Han, Zhongxiao Li, Yong Liu, Peilin Zhao, Jing Li

Collaboration Based Multi-Label Propagation for Fraud Detection

Haobo Wang, Zhao Li, Jiaming Huang, Pengrui Hui, Weiwei Liu

Recurrent Dirichlet Belief Networks for interpretable Dynamic Relational Data Modelling

Yaqiong Li, Xuhui Fan, Ling Chen, Bin Li, zheng Yu

AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search

Daoyuan Chen, Yaliang Li, Minghui Qiu, Zhen Wang, Bofang Li

Scalable Gaussian Process Regression Networks

Shibo Li, Wei Xing, Robert M. Kirby, Shandian Zhe

Neural Tensor Model for Learning Multi-Aspect Factors in Recommender Systems

Huiyuan Chen, Jing Li

Embodied Multimodal Multitask Learning

Devendra Singh Chaplot, Lisa Lee, Ruslan Salakhutdinov, Devi Parikh, Dhruv Batra

Convolutional Neural Networks with Compression Complexity Pooling for Out-of-Distribution Image Detection

Sehun Yu, Dongha Lee, Hwanjo Yu

Synthesizing Aspect-Driven Recommendation Explanations from Reviews

Trung-Hoang Le, Hady W. Lauw

Towards a Hierarchical Bayesian Model of Multi-View Anomaly Detection

Zhen Wang, Chao Lan

Learning with Labeled and Unlabeled Multi-Step Transition Data for Recovering Markov Chain from Incomplete Transition Data

Masahiro Kohjima, Takeshi Kurashima, Hiroyuki Toda

Logic Constrained Pointer Networks for Interpretable Textual Similarity

Subhadeep Maji, Rohan Kumar, Manish Bansal, Kalyani Roy, Pawan Goyal

Generalized Mean Estimation in Monte-Carlo Tree Search

Tuan Dam, Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen

Knowledge-Based Regularization in Generative Modeling

Naoya Takeishi, Yoshinobu Kawahara

Optimal Margin Distribution Machine for Multi-Instance Learning

Teng Zhang, Hai Jin

Privileged label enhancement with multi-label learning

Wenfang Zhu, Xiuyi Jia, Weiwei Li

Tensor-based multi-view label enhancement for multi-label learning

Fangwen Zhang, Xiuyi Jia, Weiwei Li

Arbitrary Talking Face Generation via Attentional Audio-Visual Coherence Learning

Hao Zhu, Huaibo Huang, Yi Li, Aihua Zheng, Ran He

LSGCN: Long Short-Term Traffic Prediction with Graph Convolutional Networks

Rongzhou Huang, Chuyin Huang, Yubao Liu, Genan Dai, Weiyang Kong

Unsupervised Monocular Visual-inertial Odometry Network

Peng Wei, Guoliang Hua, Weibo Huang, Fanyang Meng, Hong Liu

Stochastic Batch Augmentation with An Effective Distilled Dynamic Soft Label Regularizer

Qian Li, Qingyuan Hu, Yong Qi, Saiyu Qi, Jie Ma

Intention2Basket: A Neural Intention-driven Approach for Dynamic Next-basket Planning

Shoujin Wang, Liang Hu, Yan Wang, Quan Z. Sheng, Mehmet Orgun

DropNAS: Grouped Operation Dropout for Differentiable Architecture Search

Weijun Hong, Guilin Li, Weinan Zhang, Ruiming Tang, Yunhe Wang

Interpretable Models for Understanding Immersive Simulations

Nicholas Hoernle, Kobi Gal, Barbara Grosz, Leilah Lyons, Ada Ren

Complete Bottom-Up Predicate Invention in Meta-Interpretive Learning

Céline Hocquette, Stephen H. Muggleton

DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction

Alexander Schulz, Fabian Hinder, Barbara Hammer

Soft Threshold Ternary Networks

Weixiang Xu, Xiangyu He, Tianli Zhao, Qinghao Hu, Peisong Wang

KoGuN: Accelerating Deep Reinforcement Learning via Integrating Human Suboptimal Knowledge

Peng Zhang, Jianye Hao, Weixun Wang, Hongyao Tang, Yi Ma

Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation

Julian Berk, Sunil Gupta, Santu Rana, Svetha Venkatesh

FNNC: Achieving Fairness through Neural Networks

Manisha Padala, Sujit Gujar

Towards Accurate and Robust Domain Adaptation under Noisy Environments

Zhongyi Han, Xian-Jin Gui, Chaoran Cui, Yilong Yin

Fairness-Aware Neural Rényi Minimization for Continuous Features

Vincent Grari, Sylvain Lamprier, Marcin Detyniecki

Batch Decorrelation for Active Metric Learning

Priyadarshini Kumari, Ritesh Goru, Siddhartha Chaudhuri, Subhasis Chaudhuri

Online Positive and Unlabeled Learning

Chuang Zhang, Chen Gong, Tengfei LIU, Xun Lu, Weiqiang Wang

Disentangling Direct and Indirect Interactions in Polytomous Item Response Theory Models

Frank Nussbaum, Joachim Giesen

Human-Driven FOL Explanations of Deep Learning

Gabriele Ciravegna, Francesco Giannini, Marco Gori, Marco Maggini, Stefano Melacci

Effective Search of Logical Forms for Weakly Supervised Knowledge-Based Question Answering

Tao Shen, Xiubo Geng, Guodong Long, Jing Jiang, Chengqi Zhang

Best Arm Identification in Spectral Bandits

Tomáš Kocák, Aurélien Garivier

Learning Interpretable Models in the Property Specification Language

Rajarshi Roy, Dana Fisman, Daniel Neider

Can Cross Entropy Loss Be Robust to Label Noise?

Lei Feng, Senlin Shu, Zhuoyi Lin, Fengmao Lv, Li Li

Solving Hard AI Planning Instances Using Curriculum-Driven Deep Reinforcement Learning

Dieqiao Feng, Carla Gomes, Bart Selman

Knowledge Hypergraphs: Prediction Beyond Binary Relations

Bahare Fatemi, Perouz Taslakian, David Vázquez, David Poole

Location Prediction over Sparse User Mobility Traces Using RNNs: Flashback in Hidden States!

Dingqi Yang, Benjamin Fankhauser, Paolo Rosso, Philippe Cudré-Mauroux

Xiao Wang, Shaohua Fan, Kun Kuang, Chuan Shi, Jiawei Liu

Memory Augmented Neural Model for Incremental Session-based Recommendation

Fei Mi, Boi Faltings

Metric Learning in Optimal Transport for Domain Adaptation

Tanguy Kerdoncuff, Rémi Emonet, Marc Sebban

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

Non-monotone DR-submodular Maximization over General Convex Sets

Christoph Dürr, Nguyễn Kim Thắng, Abhinav Srivastav, Léo Tible

Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks

Maxime Wabartha, Audrey Durand, Vincent Francois-Lavet, Joelle Pineau

Self-paced Consensus Clustering with Bipartite Graph

Peng Zhou, Liang Du, Xuejun Li

Coloring Graph Neural Networks for Node Disambiguation

George Dasoulas, Ludovic DOS SANTOS, Kevin Scaman, Aladin Virmaux

Marthe: Scheduling the Learning Rate Via Online Hypergradients

Michele Donini, Luca Franceschi, Orchid Majumder, Massimiliano Pontil, Paolo Frasconi

Direct Quantization for Training Highly Accurate Low Bit-width Deep Neural Networks

Tuan Hoang, Thanh-Toan Do, Tam V. Nguyen, Ngai-Man Cheung

The Sparse MinMax k-Means Algorithm for High-Dimensional Clustering

Sayak Dey, Swagatam Das, Rammohan Mallipeddi

Potential Driven Reinforcement Learning for Hard Exploration Tasks

Enmin Zhao, Shihong Deng, Yifan Zang, Yongxin Kang, Kai Li

SI-VDNAS: Semi-Implicit Variational Dropout for Hierarchical One-shot Neural Architecture Search

Yaoming Wang, Wenrui Dai, Chenglin Li, Junni Zou, Hongkai Xiong

Fully Nested Neural Network for Adaptive Compression and Quantization

Yufei CUI, Ziquan Liu, Wuguannan Yao, Qiao Li, Antoni B. Chan

Learning Large Logic Programs By Going Beyond Entailment

Andrew Cropper, Sebastijan Dumancic

Flow-based Intrinsic Curiosity Module

Hsuan-Kung Yang, Po-Han Chiang, Min-Fong Hong, Chun-Yi Lee

Compressed Self-Attention for Deep Metric Learning with Low-Rank Approximation

Ziye Chen, Mingming Gong, Lingjuan Ge, Bo Du

An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles

Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani

Bayesian Decision Process for Budget-efficient Crowdsourced Clustering

Xiaozhou Wang, Xi Chen, Qihang Lin, Weidong Liu

Variational Learning of Bayesian Neural Networks via Bayesian Dark Knowledge

Gehui Shen, Xi Chen, Zhihong Deng

Switching Poisson Gamma Dynamical Systems

wenchao chen, Bo Chen, Yicheng Liu, Qianru Zhao, Mingyuan Zhou

IR-VIC: Unsupervised Discovery of Sub-goals for Transfer in RL

Nirbhay Modhe, Prithvijit Chattopadhyay, Mohit Sharma, Abhishek Das, Devi Parikh