Zhu, Xingquan

31 publications

IJCAI 2025 HGEN: Heterogeneous Graph Ensemble Networks Jiajun Shen, Yufei Jin, Kaibu Feng, Yi He, Xingquan Zhu

AAAI 2025 Metric-Agnostic Continual Learning for Sustainable Group Fairness Heng Lian, Chen Zhao, Zhong Chen, Xingquan Zhu, My T. Thai, Yi He

ICML 2025 Topology-Aware Neural Flux Prediction Guided by Physics Haoyang Jiang, Jindong Wang, Xingquan Zhu, Yi He

IJCAI 2025 Towards Fairness with Limited Demographics via Disentangled Learning Zichong Wang, Anqi Wu, Nuno Moniz, Shu Hu, Bart P. Knijnenburg, Xingquan Zhu, Wenbin Zhang

AAAI 2024 GLDL: Graph Label Distribution Learning Yufei Jin, Richard Gao, Yi He, Xingquan Zhu

NeurIPS 2024 HGDL: Heterogeneous Graph Label Distribution Learning Yufei Jin, Heng Lian, Yi He, Xingquan Zhu

ECML-PKDD 2023 ConGCN: Factorized Graph Convolutional Networks for Consensus Recommendation Boyu Li, Ting Guo, Xingquan Zhu, Yang Wang, Fang Chen

NeurIPS 2023 Structure-Free Graph Condensation: From Large-Scale Graphs to Condensed Graph-Free Data Xin Zheng, Miao Zhang, Chunyang Chen, Quoc Viet Hung Nguyen, Xingquan Zhu, Shirui Pan

IJCAI 2021 GAEN: Graph Attention Evolving Networks Min Shi, Yu Huang, Xingquan Zhu, Yufei Tang, Yuan Zhuang, Jianxun Liu

IJCAI 2020 Multi-Class Imbalanced Graph Convolutional Network Learning Min Shi, Yufei Tang, Xingquan Zhu, David A. Wilson, Jianxun Liu

IJCAI 2019 Discriminative Sample Generation for Deep Imbalanced Learning Ting Guo, Xingquan Zhu, Yang Wang, Fang Chen

IJCAI 2017 User Profile Preserving Social Network Embedding Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang

IJCAI 2016 Bernoulli Random Forests: Closing the Gap Between Theoretical Consistency and Empirical Soundness Yisen Wang, Qingtao Tang, Shu-Tao Xia, Jia Wu, Xingquan Zhu

AAAI 2016 Direct Discriminative Bag Mapping for Multi-Instance Learning Jia Wu, Shirui Pan, Peng Zhang, Xingquan Zhu

IJCAI 2016 Tri-Party Deep Network Representation Shirui Pan, Jia Wu, Xingquan Zhu, Chengqi Zhang, Yang Wang

IJCAI 2015 Multi-Graph-View Learning for Complicated Object Classification Jia Wu, Shirui Pan, Xingquan Zhu, Zhihua Cai, Chengqi Zhang

IJCAI 2013 Graph Classification with Imbalanced Class Distributions and Noise Shirui Pan, Xingquan Zhu

ECML-PKDD 2013 Knowledge Transfer for Multi-Labeler Active Learning Meng Fang, Jie Yin, Xingquan Zhu

AAAI 2012 Active Learning from Oracle with Knowledge Blind Spot Meng Fang, Xingquan Zhu, Chengqi Zhang

AAAI 2011 An Empirical Study of Bagging Predictors for Different Learning Algorithms Guohua Liang, Xingquan Zhu, Chengqi Zhang

IJCAI 2011 Cross-Domain Collaborative Filtering over Time Bin Li, Xingquan Zhu, Ruijiang Li, Chengqi Zhang, Xiangyang Xue, Xindong Wu

AAAI 2011 Large Scale Diagnosis Using Associations Between System Outputs and Components Ting Guo, Zhanshan Li, Ruizhi Guo, Xingquan Zhu

AAAI 2011 Optimal Subset Selection for Active Learning Yifan Fu, Xingquan Zhu

AAAI 2011 Tracking User-Preference Varying Speed in Collaborative Filtering Ruijiang Li, Bin Li, Cheng Jin, Xiangyang Xue, Xingquan Zhu

IJCAI 2009 Multiple Information Sources Cooperative Learning Xingquan Zhu, Ruoming Jin

IJCAI 2007 An Empirical Study of the Noise Impact on Cost-Sensitive Learning Xingquan Zhu, Xindong Wu, Taghi M. Khoshgoftaar, Yong Shi

IJCAI 2007 Mining Complex Patterns Across Sequences with Gap Requirements Xingquan Zhu, Xindong Wu

CVPR 2006 Accelerated Kernel Feature Analysis Xianhua Jiang, Yuichi Motai, Robert R. Snapp, Xingquan Zhu

AAAI 2004 Error Detection and Impact-Sensitive Instance Ranking in Noisy Datasets Xingquan Zhu, Xindong Wu, Ying Yang

ICML 2003 Eliminating Class Noise in Large Datasets Xingquan Zhu, Xindong Wu, Qijun Chen

IJCAI 2003 Mining Video Associations for Efficient Database Management Xingquan Zhu, Xindong Wu