IJCAI 2021

722 papers

Boosting Variational Inference With Locally Adaptive Step-Sizes

Gideon Dresdner, Saurav Shekhar, Fabian Pedregosa, Francesco Locatello, Gunnar Rätsch

Optimal ANN-SNN Conversion for Fast and Accurate Inference in Deep Spiking Neural Networks

Jianhao Ding, Zhaofei Yu, Yonghong Tian, Tiejun Huang

Graph-Free Knowledge Distillation for Graph Neural Networks

Xiang Deng, Zhongfei Zhang

Isotonic Data Augmentation for Knowledge Distillation

Wanyun Cui, Sen Yan

Convexified Graph Neural Networks for Distributed Control in Robotic Swarms

Saar Cohen, Noa Agmon

CuCo: Graph Representation with Curriculum Contrastive Learning

Guanyi Chu, Xiao Wang, Chuan Shi, Xunqiang Jiang

Variational Model-based Policy Optimization

Yinlam Chow, Brandon Cui, Moonkyung Ryu, Mohammad Ghavamzadeh

Time-Aware Multi-Scale RNNs for Time Series Modeling

Zipeng Chen, Qianli Ma, Zhenxi Lin

On Self-Distilling Graph Neural Network

Yuzhao Chen, Yatao Bian, Xi Xiao, Yu Rong, Tingyang Xu

Few-Shot Learning with Part Discovery and Augmentation from Unlabeled Images

Wentao Chen, Chenyang Si, Wei Wang, Liang Wang, Zilei Wang

Dependent Multi-Task Learning with Causal Intervention for Image Captioning

Wenqing Chen, Jidong Tian, Caoyun Fan, Hao He, Yaohui Jin

Monte Carlo Filtering Objectives

Shuangshuang Chen, Sihao Ding, Yiannis Karayiannidis, Mårten Björkman

Understanding Structural Vulnerability in Graph Convolutional Networks

Liang Chen, Jintang Li, Qibiao Peng, Yang Liu, Zibin Zheng

Learning Attributed Graph Representation with Communicative Message Passing Transformer

Jianwen Chen, Shuangjia Zheng, Ying Song, Jiahua Rao, Yuedong Yang

AMA-GCN: Adaptive Multi-layer Aggregation Graph Convolutional Network for Disease Prediction

Hao Chen, Fuzhen Zhuang, Li Xiao, Ling Ma, Haiyan Liu

Generative Adversarial Neural Architecture Search

Seyed Saeed Changiz Rezaei, Fred X. Han, Di Niu, Mohammad Salameh, Keith Mills

Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in a First-person Simulated 3D Environment

Wilka Carvalho, Anthony Liang, Kimin Lee, Sungryull Sohn, Honglak Lee

Thompson Sampling for Bandits with Clustered Arms

Emil Carlsson, Devdatt Dubhashi, Fredrik D. Johansson

Towards Understanding the Spectral Bias of Deep Learning

Yuan Cao, Zhiying Fang, Yue Wu, Ding-Xuan Zhou, Quanquan Gu

Partial Multi-Label Optimal Margin Distribution Machine

Nan Cao, Teng Zhang, Hai Jin

Fast Pareto Optimization for Subset Selection with Dynamic Cost Constraints

Chao Bian, Chao Qian, Frank Neumann, Yang Yu

Efficient Neural Network Verification via Layer-based Semidefinite Relaxations and Linear Cuts

Ben Batten, Panagiotis Kouvaros, Alessio Lomuscio, Yang Zheng

Optimal Algorithms for Range Searching over Multi-Armed Bandits

Siddharth Barman, Ramakrishnan Krishnamurthy, Saladi Rahul

Reconciling Rewards with Predictive State Representations

Andrea Baisero, Christopher Amato

Robustly Learning Composable Options in Deep Reinforcement Learning

Akhil Bagaria, Jason Senthil, Matthew Slivinski, George Konidaris

Verifying Reinforcement Learning up to Infinity

Edoardo Bacci, Mirco Giacobbe, David Parker

DEHB: Evolutionary Hyberband for Scalable, Robust and Efficient Hyperparameter Optimization

Noor Awad, Neeratyoy Mallik, Frank Hutter

Conditional Self-Supervised Learning for Few-Shot Classification

Yuexuan An, hui xue, Xingyu Zhao, Lu Zhang

Deep Reinforcement Learning for Navigation in AAA Video Games

Eloi Alonso, Maxim Peter, David Goumard, Joshua Romoff

Simulation of Electron-Proton Scattering Events by a Feature-Augmented and Transformed Generative Adversarial Network (FAT-GAN)

Yasir Alanazi, Nobuo Sato, Tianbo Liu, Wally Melnitchouk, Pawel Ambrozewicz

Likelihood-free Out-of-Distribution Detection with Invertible Generative Models

Amirhossein Ahmadian, Fredrik Lindsten

The Surprising Power of Graph Neural Networks with Random Node Initialization

Ralph Abboud, İsmail İlkan Ceylan, Martin Grohe, Thomas Lukasiewicz

AMEIR: Automatic Behavior Modeling, Interaction Exploration and MLP Investigation in the Recommender System

Pengyu Zhao, Kecheng Xiao, Yuanxing Zhang, Kaigui Bian, Wei Yan

Causal Discovery with Multi-Domain LiNGAM for Latent Factors

Yan Zeng, Shohei Shimizu, Ruichu Cai, Feng Xie, Michio Yamamoto

Neighborhood Intervention Consistency: Measuring Confidence for Knowledge Graph Link Prediction

Kai Wang, Yu Liu, Quan Z. Sheng

Transforming Robotic Plans with Timed Automata to Solve Temporal Platform Constraints

Tarik Viehmann, Till Hofmann, Gerhard Lakemeyer

Abstract Argumentation Frameworks with Domain Assignments

Alexandros Vassiliades, Theodore Patkos, Giorgos Flouris, Antonis Bikakis, Nick Bassiliades

Skeptical Reasoning with Preferred Semantics in Abstract Argumentation without Computing Preferred Extensions

Matthias Thimm, Federico Cerutti, Mauro Vallati

Lifting Symmetry Breaking Constraints with Inductive Logic Programming

Alice Tarzariol, Martin Gebser, Konstantin Schekotihin

Physics-informed Spline Learning for Nonlinear Dynamics Discovery

Fangzheng Sun, Yang Liu, Hao Sun

Ranking Extensions in Abstract Argumentation

Kenneth Skiba, Tjitze Rienstra, Matthias Thimm, Jesse Heyninck, Gabriele Kern-Isberner

A Description Logic for Analogical Reasoning

Steven Schockaert, Yazmín Ibáñez-García, Víctor Gutiérrez-Basulto

Inconsistency Measurement for Paraconsistent Inference

Yakoub Salhi

Efficient PAC Reinforcement Learning in Regular Decision Processes

Alessandro Ronca, Giuseppe De Giacomo

Unsupervised Knowledge Graph Alignment by Probabilistic Reasoning and Semantic Embedding

Zhiyuan Qi, Ziheng Zhang, Jiaoyan Chen, Xi Chen, Yuejia Xiang

A Ladder of Causal Distances

Maxime Peyrard, Robert West

Modeling Precomputation In Games Played Under Computational Constraints

Thomas Orton

Compressing Exact Cover Problems with Zero-suppressed Binary Decision Diagrams

Masaaki Nishino, Norihito Yasuda, Kengo Nakamura

Two Forms of Responsibility in Strategic Games

Pavel Naumov, Jia Tao

Faster Smarter Proof by Induction in Isabelle/HOL

Yutaka Nagashima

On the Relation Between Approximation Fixpoint Theory and Justification Theory

Simon Marynissen, Bart Bogaerts, Marc Denecker

Bounded Predicates in Description Logics with Counting

Sanja Lukumbuzya, Mantas Šimkus

Multi-Agent Belief Base Revision

Emiliano Lorini, François Schwarzentruber

Reasoning about Beliefs and Meta-Beliefs by Regression in an Expressive Probabilistic Action Logic

Daxin Liu, Gerhard Lakemeyer

Inferring Time-delayed Causal Relations in POMDPs from the Principle of Independence of Cause and Mechanism

Junchi Liang, Abdeslam Boularias

Scalable Non-observational Predicate Learning in ASP

Mark Law, Alessandra Russo, Krysia Broda, Elisa Bertino

Signature-Based Abduction with Fresh Individuals and Complex Concepts for Description Logics

Patrick Koopmann

Multi-Agent Abstract Argumentation Frameworks With Incomplete Knowledge of Attacks

Andreas Herzig, Antonio Yuste Ginel

HIP Network: Historical Information Passing Network for Extrapolation Reasoning on Temporal Knowledge Graph

Yongquan He, Peng Zhang, Luchen Liu, Qi Liang, Wenyuan Zhang

Using Platform Models for a Guided Explanatory Diagnosis Generation for Mobile Robots

Daniel Habering, Till Hofmann, Gerhard Lakemeyer

Updating the Belief Promotion Operator

Daniel A. Grimaldi, M. Vanina Martinez, Ricardo O. Rodriguez

Program Synthesis as Dependency Quantified Formula Modulo Theory

Priyanka Golia, Subhajit Roy, Kuldeep S. Meel

Actively Learning Concepts and Conjunctive Queries under ELr-Ontologies

Maurice Funk, Jean Christoph Jung, Carsten Lutz

Decomposition-Guided Reductions for Argumentation and Treewidth

Johannes Fichte, Markus Hecher, Yasir Mahmood, Arne Meier

Improved Algorithms for Allen's Interval Algebra: a Dynamic Programming Approach

Leif Eriksson, Victor Lagerkvist

How Hard to Tell? Complexity of Belief Manipulation Through Propositional Announcements

Thomas Eiter, Aaron Hunter, François Schwarzentruber

HyperLDLf: a Logic for Checking Properties of Finite Traces Process Logs

Giuseppe De Giacomo, Paolo Felli, Marco Montali, Giuseppe Perelli

Finite-Trace and Generalized-Reactivity Specifications in Temporal Synthesis

Giuseppe De Giacomo, Antonio Di Stasio, Lucas M. Tabajara, Moshe Vardi, Shufang Zhu

Abductive Knowledge Induction from Raw Data

Wang-Zhou Dai, Stephen Muggleton

A Uniform Abstraction Framework for Generalized Planning

Zhenhe Cui, Yongmei Liu, Kailun Luo

On Belief Change for Multi-Label Classifier Encodings

Sylvie Coste-Marquis, Pierre Marquis

Intensional and Extensional Views in DL-Lite Ontologies

Marco Console, Giuseppe De Giacomo, Maurizio Lenzerini, Manuel Namici

Abductive Learning with Ground Knowledge Base

Le-Wen Cai, Wang-Zhou Dai, Yu-Xuan Huang, Yu-feng Li, Stephen Muggleton

Budget-Constrained Coalition Strategies with Discounting

Lia Bozzone, Pavel Naumov

Cardinality Queries over DL-Lite Ontologies

Meghyn Bienvenu, Quentin Manière, Michaël Thomazo

Choice Logics and Their Computational Properties

Michael Bernreiter, Jan Maly, Stefan Woltran

Reasoning About Agents That May Know Other Agents’ Strategies

Francesco Belardinelli, Sophia Knight, Alessio Lomuscio, Bastien Maubert, Aniello Murano

On Cycles, Attackers and Supporters --- A Contribution to The Investigation of Dynamics in Abstract Argumentation

Ringo Baumann, Markus Ulbricht

A Game-Theoretic Account of Responsibility Allocation

Christel Baier, Florian Funke, Rupak Majumdar

Best-Effort Synthesis: Doing Your Best Is Not Harder Than Giving Up

Benjamin Aminof, Giuseppe De Giacomo, Sasha Rubin

Type Anywhere You Want: An Introduction to Invisible Mobile Keyboard

Sahng-Min Yoo, Ue-Hwan Kim, Yewon Hwang, Jong-Hwan Kim

Item Response Ranking for Cognitive Diagnosis

Shiwei Tong, Qi Liu, Runlong Yu, Wei Huang, Zhenya Huang

Event-based Action Recognition Using Motion Information and Spiking Neural Networks

Qianhui Liu, Dong Xing, Huajin Tang, De Ma, Gang Pan

An Entanglement-driven Fusion Neural Network for Video Sentiment Analysis

Dimitris Gkoumas, Qiuchi Li, Yijun Yu, Dawei Song

Accounting for Confirmation Bias in Crowdsourced Label Aggregation

Meric Altug Gemalmaz, Ming Yin

Human-AI Collaboration with Bandit Feedback

Ruijiang Gao, Maytal Saar-Tsechansky, Maria De-Arteaga, Ligong Han, Min Kyung Lee

Pruning of Deep Spiking Neural Networks through Gradient Rewiring

Yanqi Chen, Zhaofei Yu, Wei Fang, Tiejun Huang, Yonghong Tian

UIBert: Learning Generic Multimodal Representations for UI Understanding

Chongyang Bai, Xiaoxue Zang, Ying Xu, Srinivas Sunkara, Abhinav Rastogi

Choosing the Right Algorithm With Hints From Complexity Theory

Shouda Wang, Weijie Zheng, Benjamin Doerr

A New Upper Bound Based on Vertex Partitioning for the Maximum K-plex Problem

Hua Jiang, Dongming Zhu, Zhichao Xie, Shaowen Yao, Zhang-Hua Fu

A Runtime Analysis of Typical Decomposition Approaches in MOEA/D Framework for Many-objective Optimization Problems

Zhengxin Huang, Yuren Zhou, Chuan Luo, Qingwei Lin

Bounded-cost Search Using Estimates of Uncertainty

Maximilian Fickert, Tianyi Gu, Wheeler Ruml

DACBench: A Benchmark Library for Dynamic Algorithm Configuration

Theresa Eimer, André Biedenkapp, Maximilian Reimer, Steven Adriansen, Frank Hutter

Faster Guarantees of Evolutionary Algorithms for Maximization of Monotone Submodular Functions

Victoria G. Crawford

Knowledge-based Residual Learning

Guanjie Zheng, Chang Liu, Hua Wei, Porter Jenkins, Chacha Chen

Graph Deformer Network

Wenting Zhao, Yuan Fang, Zhen Cui, Tong Zhang, Jian Yang

Heterogeneous Graph Information Bottleneck

Liang Yang, Fan Wu, Zichen Zheng, bingxin niu, Junhua Gu

Spatial-Temporal Sequential Hypergraph Network for Crime Prediction with Dynamic Multiplex Relation Learning

Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Liefeng Bo

User-as-Graph: User Modeling with Heterogeneous Graph Pooling for News Recommendation

Chuhan Wu, Fangzhao Wu, Yongfeng Huang, Xing Xie

Federated Learning with Fair Averaging

Zheng Wang, Xiaoliang Fan, Jianzhong Qi, Chenglu Wen, Cheng Wang