IJCAI 2021

722 papers

Sensitivity Direction Learning with Neural Networks Using Domain Knowledge as Soft Shape Constraints

Kazuyuki Wakasugi

Compositional Neural Logic Programming

Son N. Tran

Dual Active Learning for Both Model and Data Selection

Ying-Peng Tang, Sheng-jun Huang

Self-supervised Network Evolution for Few-shot Classification

Xuwen Tang, Zhu Teng, Baopeng Zhang, Jianping Fan

Hyperspectral Band Selection via Spatial-Spectral Weighted Region-wise Multiple Graph Fusion-Based Spectral Clustering

Chang Tang, Xinwang Liu, En Zhu, Lizhe Wang, Albert Zomaya

Predicting Traffic Congestion Evolution: A Deep Meta Learning Approach

Yidan Sun, Guiyuan Jiang, Siew Kei Lam, Peilan He

Towards Reducing Biases in Combining Multiple Experts Online

Yi Sun, Iván Ramírez Díaz, Alfredo Cuesta Infante, Kalyan Veeramachaneni

MFNP: A Meta-optimized Model for Few-shot Next POI Recommendation

Huimin Sun, Jiajie Xu, Kai Zheng, Pengpeng Zhao, Pingfu Chao

TE-ESN: Time Encoding Echo State Network for Prediction Based on Irregularly Sampled Time Series Data

Chenxi Sun, Shenda Hong, Moxian Song, Yen-Hsiu Chou, Yongyue Sun

Neural Architecture Search of SPD Manifold Networks

Rhea Sanjay Sukthanker, Zhiwu Huang, Suryansh Kumar, Erik Goron Endsjo, Yan Wu

Positive-Unlabeled Learning from Imbalanced Data

Guangxin Su, Weitong Chen, Miao Xu

Online Risk-Averse Submodular Maximization

Tasuku Soma, Yuichi Yoshida

Unsupervised Progressive Learning and the STAM Architecture

James Smith, Cameron Taylor, Seth Baer, Constantine Dovrolis

Interpretable Compositional Convolutional Neural Networks

Wen Shen, Zhihua Wei, Shikun Huang, Binbin Zhang, Jiaqi Fan

Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness

Dazhong Shen, Chuan Qin, Chao Wang, Hengshu Zhu, Enhong Chen

Towards Robust Model Reuse in the Presence of Latent Domains

Jie-Jing Shao, Zhanzhan Cheng, Yu-feng Li, Shiliang Pu

Don’t Do What Doesn’t Matter: Intrinsic Motivation with Action Usefulness

Mathieu Seurin, Florian Strub, Philippe Preux, Olivier Pietquin

Physics-aware Spatiotemporal Modules with Auxiliary Tasks for Meta-Learning

Sungyong Seo, Chuizheng Meng, Sirisha Rambhatla, Yan Liu

Stochastic Shortest Path with Adversarially Changing Costs

Aviv Rosenberg, Yishay Mansour

Exact Acceleration of K-Means++ and K-Means||

Edward Raff

Source-free Domain Adaptation via Avatar Prototype Generation and Adaptation

Zhen Qiu, Yifan Zhang, Hongbin Lin, Shuaicheng Niu, Yanxia Liu

Multi-Agent Reinforcement Learning for Automated Peer-to-Peer Energy Trading in Double-Side Auction Market

Dawei Qiu, Jianhong Wang, Junkai Wang, Goran Strbac

Multi-version Tensor Completion for Time-delayed Spatio-temporal Data

Cheng Qian, Nikos Kargas, Cao Xiao, Lucas Glass, Nicholas Sidiropoulos

Meta-Reinforcement Learning by Tracking Task Non-stationarity

Riccardo Poiani, Andrea Tirinzoni, Marcello Restelli

Learning Aggregation Functions

Giovanni Pellegrini, Alessandro Tibo, Paolo Frasconi, Andrea Passerini, Manfred Jaeger

Two Birds with One Stone: Series Saliency for Accurate and Interpretable Multivariate Time Series Forecasting

Qingyi Pan, Wenbo Hu, Ning Chen

Explaining Deep Neural Network Models with Adversarial Gradient Integration

Deng Pan, Xin Li, Dongxiao Zhu

Learning Embeddings from Knowledge Graphs With Numeric Edge Attributes

Sumit Pai, Luca Costabello

TIDOT: A Teacher Imitation Learning Approach for Domain Adaptation with Optimal Transport

Tuan Nguyen, Trung Le, Nhan Dam, Quan Hung Tran, Truyen Nguyen

What Changed? Interpretable Model Comparison

Rahul Nair, Massimiliano Mattetti, Elizabeth Daly, Dennis Wei, Öznur Alkan

Accelerating Neural Architecture Search via Proxy Data

Byunggook Na, Jisoo Mok, Hyeokjun Choe, Sungroh Yoon

Fine-grained Generalization Analysis of Structured Output Prediction

Waleed Mustafa, Yunwen Lei, Antoine Ledent, Marius Kloft

Contrastive Losses and Solution Caching for Predict-and-Optimize

Maxime Mulamba, Jayanta Mandi, Michelangelo Diligenti, Michele Lombardi, Victor Bucarey

Details (Don't) Matter: Isolating Cluster Information in Deep Embedded Spaces

Lukas Miklautz, Lena G. M. Bauer, Dominik Mautz, Sebastian Tschiatschek, Christian Böhm

Minimization of Limit-Average Automata

Jakub Michaliszyn, Jan Otop

Evaluating Relaxations of Logic for Neural Networks: A Comprehensive Study

Mattia Medina Grespan, Ashim Gupta, Vivek Srikumar

Temporal and Object Quantification Networks

Jiayuan Mao, Zhezheng Luo, Chuang Gan, Joshua B. Tenenbaum, Jiajun Wu

Average-Reward Reinforcement Learning with Trust Region Methods

Xiaoteng Ma, Xiaohang Tang, Li Xia, Jun Yang, Qianchuan Zhao

Multi-Cause Effect Estimation with Disentangled Confounder Representation

Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li

Hierarchical Temporal Multi-Instance Learning for Video-based Student Learning Engagement Assessment

Jiayao Ma, Xinbo Jiang, Songhua Xu, Xueying Qin

Stochastic Actor-Executor-Critic for Image-to-Image Translation

Ziwei Luo, Jing Hu, Xin Wang, Siwei Lyu, Bin Kong

Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks

Gongxu Luo, Jianxin Li, Hao Peng, Carl Yang, Lichao Sun

Transfer Learning via Optimal Transportation for Integrative Cancer Patient Stratification

Ziyu Liu, Wei Shao, Jie Zhang, Min Zhang, Kun Huang

Smart Contract Vulnerability Detection: From Pure Neural Network to Interpretable Graph Feature and Expert Pattern Fusion

Zhenguang Liu, Peng Qian, Xiang Wang, LEI ZHU, Qinming He

Adversarial Spectral Kernel Matching for Unsupervised Time Series Domain Adaptation

Qiao Liu, hui xue

Two-stage Training for Learning from Label Proportions

Jiabin Liu, Bo Wang, Xin Shen, Zhiquan Qi, YingJie Tian

On the Intrinsic Differential Privacy of Bagging

Hongbin Liu, Jinyuan Jia, Neil Zhenqiang Gong

Graph Filter-based Multi-view Attributed Graph Clustering

Zhiping Lin, Zhao Kang

Residential Electric Load Forecasting via Attentive Transfer of Graph Neural Networks

Weixuan Lin, Di Wu

An Adaptive News-Driven Method for CVaR-sensitive Online Portfolio Selection in Non-Stationary Financial Markets

Qianqiao Liang, Mengying Zhu, Xiaolin Zheng, Yan Wang

SHPOS: A Theoretical Guaranteed Accelerated Particle Optimization Sampling Method

Zhijian Li, Chao Zhang, Hui Qian, Xin Du, Lingwei Peng

Pairwise Half-graph Discrimination: A Simple Graph-level Self-supervised Strategy for Pre-training Graph Neural Networks

Pengyong Li, Jun Wang, Ziliang Li, Yixuan Qiao, Xianggen Liu

Regularising Knowledge Transfer by Meta Functional Learning

Pan Li, Yanwei Fu, Shaogang Gong

TextGTL: Graph-based Transductive Learning for Semi-supervised Text Classification via Structure-Sensitive Interpolation

Chen Li, Xutan Peng, Hao Peng, Jianxin Li, Lihong Wang

RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning

Hankook Lee, Sungsoo Ahn, Seung-Woo Seo, You Young Song, Eunho Yang

Topological Uncertainty: Monitoring Trained Neural Networks through Persistence of Activation Graphs

Theo Lacombe, Yuichi Ike, Mathieu Carrière, Frederic Chazal, Marc Glisse

On Guaranteed Optimal Robust Explanations for NLP Models

Emanuele La Malfa, Rhiannon Michelmore, Agnieszka M. Zbrzezny, Nicola Paoletti, Marta Kwiatkowska

Solving Continuous Control with Episodic Memory

Igor Kuznetsov, Andrey Filchenkov

Towards Scalable Complete Verification of Relu Neural Networks via Dependency-based Branching

Panagiotis Kouvaros, Alessio Lomuscio

Epsilon Best Arm Identification in Spectral Bandits

Tomáš Kocák, Aurélien Garivier

Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation

Taehyeon Kim, Jaehoon Oh, Nak Yil Kim, sangwook Cho, Se-Young Yun

Knowledge Consolidation based Class Incremental Online Learning with Limited Data

Mohammed Asad Karim, Vinay Kumar Verma, Pravendra Singh, Vinay Namboodiri, Piyush Rai

SalientSleepNet: Multimodal Salient Wave Detection Network for Sleep Staging

Ziyu Jia, Youfang Lin, Jing Wang, Xuehui Wang, Peiyi Xie

Learning to Learn Personalized Neural Network for Ventricular Arrhythmias Detection on Intracardiac EGMs

Zhenge Jia, Zhepeng Wang, Feng Hong, Lichuan PING, Yiyu Shi

Learning CNF Theories Using MDL and Predicate Invention

Arcchit Jain, Clement Gautrais, Angelika Kimmig, Luc De Raedt

Reinforcement Learning for Route Optimization with Robustness Guarantees

Tobias Jacobs, Francesco Alesiani, Gulcin Ermis

On Explaining Random Forests with SAT

Yacine Izza, Joao Marques-Silva

On the Neural Tangent Kernel of Deep Networks with Orthogonal Initialization

Wei Huang, weitao Du, Richard Yi Da Xu

Asynchronous Active Learning with Distributed Label Querying

Sheng-jun Huang, Chen-Chen Zong, Kun-Peng Ning, Hai-Bo Ye

UniGNN: a Unified Framework for Graph and Hypergraph Neural Networks

Jing Huang, jie Yang

Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning

Hua Huang, Fanhua Shang, Yuanyuan Liu, Hongying Liu

DEEPSPLIT: An Efficient Splitting Method for Neural Network Verification via Indirect Effect Analysis

Patrick Henriksen, Alessio Lomuscio

Interpretable Minority Synthesis for Imbalanced Classification

Yi He, Fudong Lin, Xu Yuan, Nian-Feng Tzeng

Beyond the Spectrum: Detecting Deepfakes via Re-Synthesis

Yang He, Ning Yu, Margret Keuper, Mario Fritz

State-Based Recurrent SPMNs for Decision-Theoretic Planning under Partial Observability

Layton Hayes, Prashant Doshi, Swaraj Pawar, Hari Teja Tatavarti

Model-Based Reinforcement Learning for Infinite-Horizon Discounted Constrained Markov Decision Processes

Aria HasanzadeZonuzy, Dileep Kalathil, Srinivas Shakkottai

Fine-Grained Air Quality Inference via Multi-Channel Attention Model

Qilong Han, Dan Lu, Rui Chen

Riemannian Stochastic Recursive Momentum Method for non-Convex Optimization

Andi Han, Junbin Gao

Enabling Retrain-free Deep Neural Network Pruning Using Surrogate Lagrangian Relaxation

Deniz Gurevin, Mikhail Bragin, Caiwen Ding, Shanglin Zhou, Lynn Pepin

Robust Regularization with Adversarial Labelling of Perturbed Samples

Xiaohui Guo, Richong Zhang, Yaowei Zheng, Yongyi Mao

DA-GCN: A Domain-aware Attentive Graph Convolution Network for Shared-account Cross-domain Sequential Recommendation

Lei Guo, Li Tang, Tong Chen, LEI ZHU, Quoc Viet Hung Nguyen

Hindsight Value Function for Variance Reduction in Stochastic Dynamic Environment

Jiaming Guo, Rui Zhang, xishan zhang, shaohui peng, Qi Yi

Towards Understanding Deep Learning from Noisy Labels with Small-Loss Criterion

Xian-Jin Gui, Wei Wang, Zhang-Hao Tian

Learning Nash Equilibria in Zero-Sum Stochastic Games via Entropy-Regularized Policy Approximation

Yue Guan, Qifan Zhang, Panagiotis Tsiotras

The Successful Ingredients of Policy Gradient Algorithms

Sven Gronauer, Martin Gottwald, Klaus Diepold

Hierarchical Class-Based Curriculum Loss

Palash Goyal, Divya Choudhary, Shalini Ghosh

InverseNet: Augmenting Model Extraction Attacks with Training Data Inversion

Xueluan Gong, Yanjiao Chen, Wenbin Yang, Guanghao Mei, Qian Wang

Fast Multi-label Learning

Xiuwen Gong, Dong Yuan, Wei Bao

Bayesian Experience Reuse for Learning from Multiple Demonstrators

Mike Gimelfarb, Scott Sanner, Chi-Guhn Lee

Method of Moments for Topic Models with Mixed Discrete and Continuous Features

Joachim Giesen, Paul Kahlmeyer, Sören Laue, Matthias Mitterreiter, Frank Nussbaum

BOBCAT: Bilevel Optimization-Based Computerized Adaptive Testing

Aritra Ghosh, Andrew Lan

Video Summarization via Label Distributions Dual-Reward

Yongbiao Gao, Ning Xu, Xin Geng

Learning Groupwise Explanations for Black-Box Models

Jingyue Gao, Xiting Wang, Yasha Wang, Yulan Yan, Xing Xie

On the Convergence of Stochastic Compositional Gradient Descent Ascent Method

Hongchang Gao, Xiaoqian Wang, Lei Luo, Xinghua Shi

Deep Reinforcement Learning for Multi-contact Motion Planning of Hexapod Robots

Huiqiao Fu, Kaiqiang Tang, Peng Li, Wenqi Zhang, Xinpeng Wang

Contrastive Model Invertion for Data-Free Knolwedge Distillation

Gongfan Fang, Jie Song, Xinchao Wang, Chengchao Shen, Xingen Wang

BAMBOO: A Multi-instance Multi-label Approach Towards VDI User Logon Behavior Modeling

Wenping Fan, Yao Zhang, Qichen Hao, Xinya Wu, Min-ling Zhang

Jointly Learning Prices and Product Features

Ehsan Emamjomeh-Zadeh, Renato Paes Leme, Jon Schneider, Balasubramanian Sivan

Time-Series Representation Learning via Temporal and Contextual Contrasting

Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh

Automatic Translation of Music-to-Dance for In-Game Characters

Yinglin Duan, Tianyang Shi, ZHIPENG HU, Zhengxia Zou, Changjie Fan