iDEA-iSAIL Research Group

BackTime: Backdoor Attacks on Multivariate Time Series Forecasting

Xiao Lin, Zhining Liu, Dongqi Fu, Ruizhong Qiu, Hanghang Tong

Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, Vancouver, Canada (NeurIPS 2024 Spotlight)

Discrete-state Continuous-time Diffusion for Graph Generation

Zhe Xu, Ruizhong Qiu, Yuzhong Chen, Huiyuan Chen, Xiran Fan, Menghai Pan, Zhichen Zeng, Mahashweta Das, Hanghang Tong

Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, Vancouver, Canada (NeurIPS 2024)

PageRank Bandits for Link Prediction

Yikun Ban, Jiaru Zou, Zihao Li, Yunzhe Qi, Dongqi Fu, Jian Kang, Hanghang Tong, Jingrui He

Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, Vancouver, Canada (NeurIPS 2024)

Robust Neural Contextual Bandit against Adversarial Corruptions

Yunzhe Qi, Yikun Ban, Arindam Banerjee, Jingrui He

Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, Vancouver, Canada (NeurIPS 2024)

Temporal Graph Neural Tangent Kernel with Graphon-Guaranteed

Katherine Tieu, Dongqi Fu, Yada Zhu, Hendrik Hamann, Jingrui He

Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, Vancouver, Canada (NeurIPS 2024)

Towards Editing Time Series

Baoyu Jing, Shuqi Gu, Tianyu Chen, Zhiyu Yang, Dongsheng Li, Jingrui He, Kan Ren

Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, Vancouver, Canada (NeurIPS 2024)

Rare Category Analysis for Complex Data: A Review

Dawei Zhou, Jingrui He

ACM Computing Surveys

Hierarchical Multi-Marginal Optimal Transport for Network Alignment

Zhichen Zeng, Boxin Du, Si Zhang, Yinglong Xia, Zhining Liu, Hanghang Tong

Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2024)

Sterling: Synergistic Representation Learning on Bipartite Graphs

Baoyu Jing, Yuchen Yan, Kaize Ding, Chanyoung Park, Yada Zhu, Huan Liu, Hanghang Tong

Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2024)

Generalized few-shot node classification: toward an uncertainty-based solution

Zhe Xu, Kaize Ding, Yu-Xiong Wang, Huan Liu, Hanghang Tong

Knowledge and Information Systems

Conversational Question Answering with Language Models Generated Reformulations over Knowledge Graph

Lihui Liu, Blaine Hill, Boxin Du, Fei Wang, Hanghang Tong

Association for Computational Linguistics 2024, Bangkok, Thailand (ACL 2024)

Group Fairness via Group Consensus

Eunice Chan, Zhining Liu, Ruizhong Qiu, Yuheng Zhang, Ross Maciejewski, Hanghang Tong

The 2024 ACM Conference on Fairness, Accountability, and Transparency, Rio de Janeiro, Brazil (FAccT 2024)

BOBA: Byzantine-Robust Federated Learning with Label Skewness

Wenxuan Bao, Jun Wu, Jingrui He

International Conference on Artificial Intelligence and Statistics 2024, Palau de Congressos, Valencia, Spain (AISTATS 2024)

Class-Imbalanced Graph Learning without Class Rebalancing

Zhining Liu, Ruizhong Qiu, Zhichen Zeng, Hyunsik Yoo, David Zhou, Zhe Xu, Yada Zhu, Kommy Weldemariam, Jingrui He, Hanghang Tong

The 41st International Conference on Machine Learning, Vienna, Austria (ICML 2024)

Gradient Compressed Sensing: A Query-Efficient Gradient Estimator for High-Dimensional Zeroth-Order Optimization

Zhining Liu, Ruizhong Qiu, Zhichen Zeng, Hyunsik Yoo, David Zhou, Zhe Xu, Yada Zhu, Kommy Weldemariam, Jingrui He, Hanghang Tong

The 41st International Conference on Machine Learning, Vienna, Austria (ICML 2024)

Graph Mixup on Approximate Gromov-Wasserstein Geodesics

Zhichen Zeng, Ruizhong Qiu, Zhe Xu, Zhining Liu, Yuchen Yan, Tianxin Wei, Lei Ying, Jingrui He

The 41st International Conference on Machine Learning, Vienna, Austria (ICML 2024)

SLOG: An Inductive Spectral Graph Neural Network Beyond Polynomial Filter

Haobo Xu, Yuchen Yan, Dingsu Wang, Zhe Xu, Zhichen Zeng, Tarek F. Abdelzaher, Jiawei Han, Hanghang Tong

The 41st International Conference on Machine Learning, Vienna, Austria (ICML 2024)

Fairgen: Towards Fair Graph Generation

Lecheng Zheng, Dawei Zhou, Hanghang Tong, Jiejun Xu, Yada Zhu, Jingrui He

40th IEEE International Conference on Data Engineering, Utrecht, The Netherlands (ICDE 2024)

AIM: Attributing, Interpreting, Mitigating Data Unfairness

Zhining Liu, Ruizhong Qiu, Zhichen Zeng, Yada Zhu, Hendrik F. Hamann, Hanghang Tong

The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, Spain (KDD 2024)

Distributional Network of Networks for Modeling Data Heterogeneity

Jun Wu, Jingrui He, Hanghang Tong

The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, Spain (KDD 2024)

Meta Clustering of Neural Bandits

Yikun Ban, Yunzhe Qi, Tianxin Wei, Lihui Liu, Jingrui He

The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, Spain (KDD 2024)

Heterogeneous Contrastive Learning for Foundation Models and Beyond

Lecheng Zheng, Baoyu Jing, Zihao Li, Hanghang Tong, Jingrui He

Tutorial. The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, Spain (KDD 2024)

SpherE: Expressive and Interpretable Knowledge Graph Embedding for Set Retrieval

Zihao Li, Yuyi Ao, Jingrui He

The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, Washington DC, USA (SIGIR 2024)

FairIF: Boosting Fairness in Deep Learning via Influence Functions with Validation Set Sensitive Attributes

Haonan Wang, Ziwei Wu, Jingrui He

The 17th ACM International Conference on Web Search and Data Mining, Merida, Mexico (WSDM 2024)

Ginkgo-P: General Illustrations of Knowledge Graphs for Openness as a Platform

Blaine Hill, Lihui Liu, Hanghang Tong

The 17th ACM International Conference on Web Search and Data Mining, Merida, Mexico (WSDM 2024)

Co-clustering for Federated Recommender System

Xinrui He, Shuo Liu, Jacky Keung, Jingrui He

The International World Wide Web Conference 2024, Singapore (WWW 2024)

Ensuring User-side Fairness in Dynamic Recommender Systems

Hyunsik Yoo, Zhichen Zeng, Jian Kang, Ruizhong Qiu, David Zhou, Zhining Liu, Fei Wang, Charlie Xu, Eunice Chan, Hanghang Tong

The International World Wide Web Conference 2024, Singapore (WWW 2024)

MULAN: Multi-modal Causal Structure Learning and Root Cause Analysis for Microservice Systems

Lecheng Zheng, Zhengzhang Chen, Jingrui He, Haifeng Chen

The International World Wide Web Conference 2024, Singapore (WWW 2024)

Neural Contextual Bandits for Personalized Recommendation

Yikun Ban, Yunzhe Qi, Jingrui He

Tutorial. The International World Wide Web Conference 2024, Singapore (WWW 2024)

New Frontiers of Knowledge Graph Reasoning: Recent Advances and Future Trends

Lihui Liu, Zihao Wang, Jiaxin Bai, Yangqiu Song, Hanghang Tong

Tutorial. The International World Wide Web Conference 2024, Singapore (WWW 2024)

PaCEr: Network Embedding From Positional to Structural

Yuchen Yan, Yongyi Hu, Qinghai Zhou, Lihui Liu, Zhichen Zeng, Yuzhong Chen, Menghai Pan, Huiyuan Chen, Mahashweta Das, Hanghang Tong

The International World Wide Web Conference 2024, Singapore (WWW 2024)

TrustLOG: The Second Workshop on Trustworthy Learning on Graphs

Jingrui He, Jian Kang, Fatemeh Nargesian, Haohui Wang, An Zhang, Dawei Zhou

Workshop. The International World Wide Web Conference 2024, Singapore (WWW 2024)

Deceptive Fairness Attacks on Graphs via Meta Learning

Jian Kang, Yinglong Xia, Ross Maciejewski, Jiebo Luo, Hanghang Tong

The 12th International Conference on Learning Representations, Vienna, Austria (ICLR 2024)

Neural Active Learning Beyond Bandits

Yikun Ban, Ishika Agarwal, Ziwei Wu, Yada Zhu, Kommy Weldemariam, Hanghang Tong, Jingrui He

The 12th International Conference on Learning Representations, Vienna, Austria (ICLR 2024)

VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections

Dongqi Fu, Zhigang Hua, Yan Xie, Jin Fang, Si Zhang, Kaan Sancak, Hao Wu, Andrey Malevich, Jingrui He, Bo Long

The 12th International Conference on Learning Representations, Vienna, Austria (ICLR 2024)

Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond

Tianxin Wei, Bowen Jin, Ruirui Li, Hansi Zeng, Zhengyang Wang, Jianhui Sun, Qingyu Yin, Hanqing Lu, Suhang Wang, Jingrui He, Xianfeng Tang

The 12th International Conference on Learning Representations, Vienna, Austria (ICLR 2024)

Adaptive Test-Time Personalization for Federated Learning

Wenxuan Bao, Tianxin Wei, Haohan Wang, Jingrui He

Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2023, New Orleans, LA, USA (NeurIPS 2023)

From Trainable Negative Depth to Edge Heterophily in Graphs

Yuchen Yan, Yuzhong Chen, Huiyuan Chen, Minghua Xu, Mahashweta Das, Hao Yang, Hanghang Tong

Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2023, New Orleans, LA, USA (NeurIPS 2023)

Graph-Structured Gaussian Processes for Transferable Graph Learning

Jun Wu, Lisa Ainsworth, Andrew Leakey, Haixun Wang, Jingrui He

Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2023, New Orleans, LA, USA (NeurIPS 2023)

Meta-Learning with Neural Bandit Scheduler

Yunzhe Qi, Yikun Ban, Tianxin Wei, Jiaru Zou, Huaxiu Yao, Jingrui He

Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2023, New Orleans, LA, USA (NeurIPS 2023)

Reconciling Competing Sampling Strategies of Network Embedding

Yuchen Yan, Baoyu Jing, Lihui Liu, Ruijie Wang, Jinning Li, Tarek F. Abdelzaher, Hanghang Tong

Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2023, New Orleans, LA, USA (NeurIPS 2023)

BeMap: Balanced Message Passing for Fair Graph Neural Network

Xiao Lin, Jian Kang, Weilin Cong, Hanghang Tong

The Second Learning on Graphs Conference (LoG 2023)

Adversarial Attacks on Multi-Network Mining: Problem Definition and Fast Solutions

Qinghai Zhou, Liangyue Li, Nan Cao, Lei Ying, Hanghang Tong

IEEE Transactions on Knowledge and Data Engineering (TKDE 2023)

Non-IID Transfer Learning on Graphs

Jun Wu, Jingrui He, Elizabeth A. Ainsworth

Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023)

A Unified Framework for Adversarial Attacks on Multi-Source Domain Adaptation

Jun Wu, Jingrui He

IEEE Transactions on Knowledge and Data Engineering (TKDE 2023)

Privacy-Preserving Graph Machine Learning from Data to Computation: A Survey

Dongqi Fu, Wenxuan Bao, Ross Maciejewski, Hanghang Tong, Jingrui He

SIGKDD Explorations

Geometric Matrix Completion via Sylvester Multi-Graph Neural Network

Boxin Du, Changhe Yuan, Fei Wang, Hanghang Tong

The 32nd ACM International Conference on Information and Knowledge Management, Birmingham, United Kingdom (CIKM 2023)

Learning Node Abnormality with Weak Supervision

Qinghai Zhou, Kaize Ding, Huan Liu, Hanghang Tong

The 32nd ACM International Conference on Information and Knowledge Management, Birmingham, United Kingdom (CIKM 2023)

Robust Basket Recommendation via Noise-tolerated Graph Contrastive Learning

Xinrui He, Tianxin Wei, Jingrui He

The 32nd ACM International Conference on Information and Knowledge Management, Birmingham, United Kingdom (CIKM 2023)

Generative Graph Dictionary Learning

Zhichen Zeng, Ruike Zhu, Yinglong Xia, Hanqing Zeng, Hanghang Tong

The 41st International Conference on Machine Learning, Honolulu, Hawaii, USA (ICML 2023)

NTK-approximating MLP Fusion for Efficient Language Model Fine-tuning

Tianxin Wei, Zeming Guo, Yifan Chen, Jingrui He

The 41st International Conference on Machine Learning, Honolulu, Hawaii, USA (ICML 2023)

Optimizing the Collaboration Structure in Cross-Silo Federated Learning

Wenxuan Bao, Haohan Wang, Jun Wu, Jingrui He

The 41st International Conference on Machine Learning, Honolulu, Hawaii, USA (ICML 2023)

Graph Neural Bandits

Yunzhe Qi, Yikun Ban, Jingrui He

The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, CA, USA (KDD 2023)

Kernel Ridge Regression-Based Graph Dataset Distillation

Zhe Xu, Yuzhong Chen, Qinghai Zhou, Yuhang Wu, Menghai Pan, Hao Yang, Hanghang Tong

The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, CA, USA (KDD 2023)

Knowledge Graph Reasoning and Its Applications

Lihui Liu, Hanghang Tong

Tutorial. The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, CA, USA (KDD 2023)

Node Classification Beyond Homophily: Towards a General Solution

Zhe Xu, Yuzhong Chen, Qinghai Zhou, Yuhang Wu, Menghai Pan, Hao Yang, Hanghang Tong

The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, CA, USA (KDD 2023)

Personalized Federated Learning with Parameter Propagation

Jun Wu, Wenxuan Bao, Elizabeth A. Ainsworth, Jingrui He

The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, CA, USA (KDD 2023)

Reconstructing Graph Diffusion History from a Single Snapshot

Ruizhong Qiu, Dingsu Wang, Lei Ying, H. Vincent Poor, Yifang Zhang, Hanghang Tong

The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, CA, USA (KDD 2023)

The 3rd Workshop on Graph Learning Benchmarks (GLB 2023)

Jiaqi Ma, Jiong Zhu, Yuxiao Dong, Danai Koutra, Jingrui He, Qiaozhu Mei, Anton Tsitsulin, Xingjian Zhang, Marinka Zitnik

Workshop. The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, CA, USA (KDD 2023)

Trustworthy Transfer Learning: Transferability and Trustworthiness

Jun Wu, Jingrui He

Tutorial. The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, CA, USA (KDD 2023)

Natural and Artificial Dynamics in GNNs: A Tutorial

Dongqi Fu, Zhe Xu, Hanghang Tong, Jingrui He

Tutorial. The 16th ACM International Conference on Web Search and Data Mining, Singapore (WSDM 2023)

Everything Evolves in Personalized PageRank

Zihao Li, Dongqi Fu, Jingrui He

The International World Wide Web Conference 2023, Austin, TX, USA (WWW 2023)

Fairness-Aware Clique-Preserving Spectral Clustering of Temporal Graphs

Dongqi Fu, Dawei Zhou, Ross Maciejewski, Arie Croitoru, Marcus Boyd, Jingrui He

The International World Wide Web Conference 2023, Austin, TX, USA (WWW 2023)

Knowledge Graph Question Answering with Ambiguous Query

Lihui Liu, Yuzhong Chen, Mahashweta Das, Hao Yang, Hanghang Tong

The International World Wide Web Conference 2023, Austin, TX, USA (WWW 2023)

PARROT: Position-Aware Regularized Optimal Transport for Network Alignment

Zhichen Zeng, Si Zhang, Yinglong Xia, Hanghang Tong

The International World Wide Web Conference 2023, Austin, TX, USA (WWW 2023)

Natural and Artificial Dynamics in Graphs: Concept, Progress, and Future

Dongqi Fu, Jingrui He

Frontiers in Big Data, Volume 5

Dynamic transfer learning with progressive meta-task scheduler

Jun Wu, Jingrui He

Frontiers in Big Data, Volume 5

Knowledge Graph Comparative Reasoning for Fact Checking: Problem Definition and Algorithms

Lihui Liu, Ruining Zhao, Boxin Du, Yi Ren Fung, Heng Ji, Jiejun Xu, Hanghang Tong

IEEE Data Engineering Bulletin, Volume 45

Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative

Tianxin Wei, Yuning You, Tianlong Chen, Yang Shen, Jingrui He, Zhangyang Wang

Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2022, New Orleans, LA, USA (NeurIPS 2022)

Deep Active Learning by Leveraging Training Dynamics

Haonan Wang, Wei Huang, Ziwei Wu, Hanghang Tong, Andrew Margenot, Jingrui He

Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2022, New Orleans, LA, USA (NeurIPS 2022)

Distribution-Informed Neural Networks for Domain Adaptation Regression

Jun Wu, Jingrui He, Sheng Wang, Kaiyu Guan, Elizabeth A. Ainsworth

Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2022, New Orleans, LA, USA (NeurIPS 2022)

Improved Algorithms for Neural Active Learning

Yikun Ban, Yuheng Zhang, Hanghang Tong, Arindam Banerjee, Jingrui He

Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2022, New Orleans, LA, USA (NeurIPS 2022)

Adaptive Knowledge Transfer on Evolving Domains

Jun Wu, Hanghang Tong, Elizabeth A. Ainsworth, Jingrui He

IEEE International Conference on Big Data, Big Data 2022, Osaka, Japan (BigData 2022)

Comparative Reasoning for Knowledge Graph Fact Checking

Lihui Liu, Houxiang Ji, Jiejun Xu, Hanghang Tong

IEEE International Conference on Big Data, Big Data 2022, Osaka, Japan (BigData 2022)

DPPIN: A Biological Repository of Dynamic Protein-Protein Interaction Network Data

Dongqi Fu, Jingrui He

IEEE International Conference on Big Data, Big Data 2022, Osaka, Japan (BigData 2022)

iFiG: Individually Fair Multi-view Graph Clustering

Yian Wang, Jian Kang, Yinglong Xia, Jiebo Luo, Hanghang Tong

IEEE International Conference on Big Data, Big Data 2022, Osaka, Japan (BigData 2022)

InfoFair: Information-Theoretic Intersectional Fairness

Jian Kang, Tiankai Xie, Xintao Wu, Ross Maciejewski, Hanghang Tong

IEEE International Conference on Big Data, Big Data 2022, Osaka, Japan (BigData 2022)

Self-supervised Hypergraph Representation Learning

Boxin Du, Changhe Yuan, Robert A. Barton, Tal Neiman, Hanghang Tong

IEEE International Conference on Big Data, Big Data 2022, Osaka, Japan (BigData 2022)

Adversarial Robustness through Bias Variance Decomposition: A New Perspective for Federated Learning

Yao Zhou, Jun Wu, Haixun Wang, Jingrui He

The 31st ACM International Conference on Information and Knowledge Management, Atlanta, GA, USA (CIKM 2022)

Dissecting Cross-Layer Dependency Inference on Multi-Layered Inter-Dependent Networks

Yuchen Yan, Qinghai Zhou, Jinning Li, Tarek F. Abdelzaher, Hanghang Tong

The 31st ACM International Conference on Information and Knowledge Management, Atlanta, GA, USA (CIKM 2022)

DISCO: Comprehensive and Explainable Disinformation Detection

Dongqi Fu, Yikun Ban, Hanghang Tong, Ross Maciejewski, Jingrui He

The 31st ACM International Conference on Information and Knowledge Management, Atlanta, GA, USA (CIKM 2022)

MentorGNN: Deriving Curriculum for Pre-Training GNNs

Dawei Zhou, Lecheng Zheng, Dongqi Fu, Jiawei Han, Jingrui He

The 31st ACM International Conference on Information and Knowledge Management, Atlanta, GA, USA (CIKM 2022)

SuGeR: A Subgraph-based Graph Convolutional Network Method for Bundle Recommendation

Zhenning Zhang, Boxin Du, Hanghang Tong

The 31st ACM International Conference on Information and Knowledge Management, Atlanta, GA, USA (CIKM 2022)

TrustLOG: The First Workshop on Trustworthy Learning on Graphs

Jian Kang, Shuaicheng Zhang, Bo Li, Jingrui He, Jian Pei, Dawei Zhou

Workshop. The 31st ACM International Conference on Information and Knowledge Management, Atlanta, GA, USA (CIKM 2022)

X-GOAL: Multiplex Heterogeneous Graph Prototypical Contrastive Learning

Yuchen Yan, Qinghai Zhou, Jinning Li, Tarek F. Abdelzaher, Hanghang Tong

The 31st ACM International Conference on Information and Knowledge Management, Atlanta, GA, USA (CIKM 2022)

Active Heterogeneous Graph Neural Networks with Per-step Meta-Q-Learning

Yuheng Zhang, Yinglong Xia, Yan Zhu, Yuejie Chi, Lei Ying, Hanghang Tong

IEEE International Conference on Data Mining, ICDM 2022, Orlando, FL, USA (ICDM 2022)

Generalized Few-Shot Node Classification

Zhe Xu, Kaize Ding, Yu-Xiong Wang, Huan Liu, Hanghang Tong

IEEE International Conference on Data Mining, ICDM 2022, Orlando, FL, USA (ICDM 2022)

Fairness-aware Model-agnostic Positive and Unlabeled Learning

Ziwei Wu, Jingrui He

The 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea (FaccT 2022 Outstanding Paper)

Algorithmic Fairness on Graphs: Methods and Trends

Jian Kang, Hanghang Tong

Tutorial. The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA (KDD 2022)