IJCAI 2022

862 papers

Tessellation-Filtering ReLU Neural Networks

Bernhard A. Moser, Michal Lewandowski, Somayeh Kargaran, Werner Zellinger, Battista Biggio

COMET Flows: Towards Generative Modeling of Multivariate Extremes and Tail Dependence

Andrew McDonald, Pang-Ning Tan, Lifeng Luo

Game Redesign in No-regret Game Playing

Yuzhe Ma, Young Wu, Xiaojin Zhu

Locally Normalized Soft Contrastive Clustering for Compact Clusters

Xin Ma, Won Hwa Kim

Deep Graph Matching for Partial Label Learning

Gengyu Lyu, Yanan Wu, Songhe Feng

Towards Robust Unsupervised Disentanglement of Sequential Data — A Case Study Using Music Audio

Yin-Jyun Luo, Sebastian Ewert, Simon Dixon

Teaching LTLf Satisfiability Checking to Neural Networks

Weilin Luo, Hai Wan, Jianfeng Du, Xiaoda Li, Yuze Fu

Exploring Binary Classification Hidden within Partial Label Learning

Hengheng Luo, Yabin Zhang, Suyun Zhao, Hong Chen, Cuiping Li

SELC: Self-Ensemble Label Correction Improves Learning with Noisy Labels

Yangdi Lu, Wenbo He

Projected Gradient Descent Algorithms for Solving Nonlinear Inverse Problems with Generative Priors

Zhaoqiang Liu, JUN HAN

Declaration-based Prompt Tuning for Visual Question Answering

Yuhang Liu, Wei Wei, Daowan Peng, Feida Zhu

JueWu-MC: Playing Minecraft with Sample-efficient Hierarchical Reinforcement Learning

Zichuan Lin, Junyou Li, Jianing Shi, Deheng Ye, Qiang Fu

Contrastive Multi-view Hyperbolic Hierarchical Clustering

Fangfei Lin, Bing Bai, Kun Bai, Yazhou Ren, Peng Zhao

Rethinking the Setting of Semi-supervised Learning on Graphs

Ziang Li, Ming Ding, Weikai Li, Zihan Wang, Ziyu Zeng

Pruning-as-Search: Efficient Neural Architecture Search via Channel Pruning and Structural Reparameterization

Yanyu Li, Pu Zhao, Geng Yuan, Xue Lin, Yanzhi Wang

Neural PCA for Flow-Based Representation Learning

Shen Li, Bryan Hooi

Cross-modal Representation Learning and Relation Reasoning for Bidirectional Adaptive Manipulation

Lei Li, Kai Fan, Chun Yuan

Learning from Students: Online Contrastive Distillation Network for General Continual Learning

Jin Li, Zhong Ji, Gang Wang, Qiang Wang, Feng Gao

Ridgeless Regression with Random Features

Jian Li, Yong Liu, Yingying Zhang

Learning General Gaussian Mixture Model with Integral Cosine Similarity

Guanglin Li, Bin Li, Changsheng Chen, Shunquan Tan, Guoping Qiu

SGAT: Simplicial Graph Attention Network

See Hian Lee, Feng Ji, Wee Peng Tay

Libra-CAM: An Activation-Based Attribution Based on the Linear Approximation of Deep Neural Nets and Threshold Calibration

Sangkyun Lee, Sungmin Han

Pseudo-spherical Knowledge Distillation

Kyungmin Lee, Hyeongkeun Lee

Multi-policy Grounding and Ensemble Policy Learning for Transfer Learning with Dynamics Mismatch

Hyun-Rok Lee, Ram Ananth Sreenivasan, Yeonjeong Jeong, Jongseong Jang, Dongsub Shim

Thompson Sampling for Bandit Learning in Matching Markets

Fang Kong, Junming Yin, Shuai Li

DyGRAIN: An Incremental Learning Framework for Dynamic Graphs

Seoyoon Kim, Seongjun Yun, Jaewoo Kang

Self-Predictive Dynamics for Generalization of Vision-based Reinforcement Learning

Kyungsoo Kim, Jeongsoo Ha, Yusung Kim

Data Augmentation for Learning to Play in Text-Based Games

Jinhyeon Kim, Kee-eung Kim

Relational Abstractions for Generalized Reinforcement Learning on Symbolic Problems

Rushang Karia, Siddharth Srivastava

Set Interdependence Transformer: Set-to-Sequence Neural Networks for Permutation Learning and Structure Prediction

Mateusz Jurewicz, Leon Derczynski

Online Evasion Attacks on Recurrent Models:The Power of Hallucinating the Future

Byunggill Joe, Insik Shin, Jihun Hamm

Graph Masked Autoencoder Enhanced Predictor for Neural Architecture Search

Kun Jing, Jungang Xu, Pengfei Li

On the Channel Pruning using Graph Convolution Network for Convolutional Neural Network Acceleration

Di Jiang, Yuan Cao, Qiang Yang

Robust Reinforcement Learning as a Stackelberg Game via Adaptively-Regularized Adversarial Training

Peide Huang, Mengdi Xu, Fei Fang, Ding Zhao

FLS: A New Local Search Algorithm for K-means with Smaller Search Space

Junyu Huang, Qilong Feng, Ziyun Huang, Jinhui Xu, Jianxin Wang

Reconstructing Diffusion Networks from Incomplete Data

Hao Huang, Keqi Han, Beicheng Xu, Ting Gan

Type-aware Embeddings for Multi-Hop Reasoning over Knowledge Graphs

Zhiwei Hu, Victor Gutierrez Basulto, Zhiliang Xiang, Xiaoli Li, Ru Li

Enhancing Unsupervised Domain Adaptation via Semantic Similarity Constraint for Medical Image Segmentation

Tao Hu, Shiliang Sun, Jing Zhao, Dongyu Shi

SHAPE: An Unified Approach to Evaluate the Contribution and Cooperation of Individual Modalities

Pengbo Hu, Xingyu Li, Yi Zhou

Learning Continuous Graph Structure with Bilevel Programming for Graph Neural Networks

Minyang Hu, Hong Chang, Bingpeng MA, Shiguang Shan

Leveraging Class Abstraction for Commonsense Reinforcement Learning via Residual Policy Gradient Methods

Niklas Hopner, Ilaria Tiddi, Herke van Hoof

To Trust or Not To Trust Prediction Scores for Membership Inference Attacks

Dominik Hintersdorf, Lukas Struppek, Kristian Kersting

Option Transfer and SMDP Abstraction with Successor Features

Dongge Han, Sebastian Tschiatschek

RoboGNN: Robustifying Node Classification under Link Perturbation

Sheng Guan, Hanchao Ma, Yinghui Wu

Sample Complexity Bounds for Robustly Learning Decision Lists against Evasion Attacks

Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell

Attributed Graph Clustering with Dual Redundancy Reduction

Lei Gong, sihang zhou, Wenxuan Tu, Xinwang Liu

Learning First-Order Rules with Differentiable Logic Program Semantics

Kun Gao, Katsumi Inoue, Yongzhi Cao, Hanpin Wang

Bootstrapping Informative Graph Augmentation via A Meta Learning Approach

Hang Gao, Jiangmeng Li, Wenwen Qiang, Lingyu Si, Fuchun Sun

A Reinforcement Learning-Informed Pattern Mining Framework for Multivariate Time Series Classification

Ge Gao, Qitong Gao, Xi Yang, Miroslav Pajic, Min Chi

Multi-view Unsupervised Graph Representation Learning

Jiangzhang Gan, Rongyao Hu, Mengmeng Zhan, Yujie Mo, Yingying Wan

DeepExtrema: A Deep Learning Approach for Forecasting Block Maxima in Time Series Data

Asadullah Hill Galib, Andrew McDonald, Tyler Wilson, Lifeng Luo, Pang-Ning Tan

Non-Cheating Teaching Revisited: A New Probabilistic Machine Teaching Model

Cesar Ferri, José Hernández-Orallo, Jan Arne Telle

Comparison Knowledge Translation for Generalizable Image Classification

Zunlei Feng, Tian Qiu, Sai Wu, Xiaotuan Jin, Zengliang He

Learning Unforgotten Domain-Invariant Representations for Online Unsupervised Domain Adaptation

Cheng Feng, Chaoliang Zhong, Jie Wang, Ying Zhang, Jun Sun

Multi-Vector Embedding on Networks with Taxonomies

Yue Fan, Xiuli Ma

Function-words Adaptively Enhanced Attention Networks for Few-Shot Inverse Relation Classification

Chunliu Dou, Shaojuan Wu, Xiaowang Zhang, Zhiyong Feng, Kewen Wang

Residual Contrastive Learning for Image Reconstruction: Learning Transferable Representations from Noisy Images

Nanqing Dong, Matteo Maggioni, Yongxin Yang, Eduardo Pérez-Pellitero, Ales Leonardis

Taylor-Lagrange Neural Ordinary Differential Equations: Toward Fast Training and Evaluation of Neural ODEs

Franck Djeumou, Cyrus Neary, Eric Goubault, Sylvie Putot, Ufuk Topcu

Coherent Probabilistic Aggregate Queries on Long-horizon Forecasts

Prathamesh Deshpande, Sunita Sarawagi

Reinforcement Learning with Option Machines

Floris den Hengst, Vincent Francois-Lavet, Mark Hoogendoorn, Frank van Harmelen

Multiband VAE: Latent Space Alignment for Knowledge Consolidation in Continual Learning

Kamil Deja, Paweł Wawrzyński, Wojciech Masarczyk, Daniel Marczak, Tomasz Trzcinski

Geometric Transformer for End-to-End Molecule Properties Prediction

Yoni Choukroun, Lior Wolf

Can We Find Neurons that Cause Unrealistic Images in Deep Generative Networks?

Hwanil Choi, Wonjoon Chang, Jaesik Choi

Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning

Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, Dimitrios Dimitriadis

Better Embedding and More Shots for Few-shot Learning

Ziqiu Chi, Zhe Wang, mengping yang, Wei Guo, Xinlei Xu

DDDM: A Brain-Inspired Framework for Robust Classification

Xiyuan Chen, Xingyu Li, Yi Zhou, Tianming Yang

Self-Supervised Mutual Learning for Dynamic Scene Reconstruction of Spiking Camera

Shiyan Chen, Chaoteng Duan, Zhaofei Yu, Ruiqin Xiong, Tiejun Huang

Rethinking the Promotion Brought by Contrastive Learning to Semi-Supervised Node Classification

Deli Chen, Yankai Lin, Lei Li, Xuancheng Ren, Peng Li

Neural Contextual Anomaly Detection for Time Series

Chris U. Carmona, Francois-Xavier Aubet, Valentin Flunkert, Jan Gasthaus

Posistive-Unlabeled Learning via Optimal Transport and Margin Distribution

Nan Cao, Teng Zhang, Xuanhua Shi, Hai Jin

Not a Number: Identifying Instance Features for Capability-Oriented Evaluation

Ryan Burnell, John Burden, Danaja Rutar, Konstantinos Voudouris, Lucy Cheke

Adversarial Explanations for Knowledge Graph Embeddings

Patrick Betz, Christian Meilicke, Heiner Stuckenschmidt

Logit Mixing Training for More Reliable and Accurate Prediction

Duhyeon Bang, Kyungjune Baek, JiWoo Kim, Yunho Jeon, Jin-Hwa Kim

One Weird Trick to Improve Your Semi-Weakly Supervised Semantic Segmentation Model

Wonho Bae, Junhyug Noh, Milad Jalali Asadabadi, Danica J. Sutherland

Fixed-Budget Best-Arm Identification in Structured Bandits

MohammadJavad Azizi, Branislav Kveton, Mohammad Ghavamzadeh

Learning Label Initialization for Time-Dependent Harmonic Extension.

Amitoz Azad

Synthesis of Maximally Permissive Strategies for LTLf Specifications

Shufang Zhu, Giuseppe De Giacomo

FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server

Hong Zhang, Ji Liu, Juncheng Jia, Yang Zhou, Huaiyu Dai

GL-RG: Global-Local Representation Granularity for Video Captioning

Liqi Yan, Qifan Wang, Yiming Cui, Fuli Feng, Xiaojun Quan

Human Parity on CommonsenseQA: Augmenting Self-Attention with External Attention

Yichong Xu, Chenguang Zhu, Shuohang Wang, Siqi Sun, Hao Cheng

Simple and Effective Relation-based Embedding Propagation for Knowledge Representation Learning

Huijuan Wang, Siming Dai, Weiyue Su, Hui Zhong, Zeyang Fang

Updating Probability Intervals with Uncertain Inputs

Karim Tabia

Considering Constraint Monotonicity and Foundedness in Answer Set Programming

Yi-Dong Shen, Thomas Eiter

Revision by Comparison for Ranking Functions

Meliha Sezgin, Gabriele Kern-Isberner

Learning Higher-Order Logic Programs From Failures

Stanisław J. Purgał, David M. Cerna, Cezary Kaliszyk

Inverse Problems for Gradual Semantics

Nir Oren, Bruno Yun, Srdjan Vesic, Murilo Baptista

Causes of Effects: Learning Individual Responses from Population Data

Scott Mueller, Ang Li, Judea Pearl

Explanations for Negative Query Answers under Inconsistency-Tolerant Semantics

Thomas Lukasiewicz, Enrico Malizia, Cristian Molinaro

Search Space Expansion for Efficient Incremental Inductive Logic Programming from Streamed Data

Mark Law, Krysia Broda, Alessandra Russo

Conditional Independence for Iterated Belief Revision

Gabriele Kern-Isberner, Jesse Heyninck, Christoph Beierle

In Data We Trust: The Logic of Trust-Based Beliefs

Junli Jiang, Pavel Naumov

The Egocentric Logic of Preferences

Junli Jiang, Pavel Naumov

Computing Concept Referring Expressions for Queries on Horn ALC Ontologies

Moritz Illich, Birte Glimm

Lexicographic Entailment, Syntax Splitting and the Drowning Problem

Jesse Heyninck, Gabriele Kern-Isberner, Thomas Meyer

Possibilistic Logic Underlies Abstract Dialectical Frameworks

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

A Computationally Grounded Logic of 'Seeing-to-it-that'

Andreas Herzig, Emiliano Lorini, Elise Perrotin

Linear Temporal Logic Modulo Theories over Finite Traces

Luca Geatti, Alessandro Gianola, Nicola Gigante

Simulating Sets in Answer Set Programming

Sarah Alice Gaggl, Philipp Hanisch, Markus Krötzsch

Frontiers and Exact Learning of ELI Queries under DL-Lite Ontologies

Maurice Funk, Jean Christoph Jung, Carsten Lutz

Plausibility Reasoning via Projected Answer Set Counting - A Hybrid Approach

Johannes K. Fichte, Markus Hecher, Mohamed A. Nadeem