Zhang, Chengqi

53 publications

ICLR 2025 Biologically Plausible Brain Graph Transformer Ciyuan Peng, Yuelong Huang, Qichao Dong, Shuo Yu, Feng Xia, Chengqi Zhang, Yaochu Jin

ICML 2025 Efficient Personalized Adaptation for Physiological Signal Foundation Model Chenrui Wu, Haishuai Wang, Xiang Zhang, Chengqi Zhang, Jiajun Bu

ICML 2025 Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning Puning Yang, Qizhou Wang, Zhuo Huang, Tongliang Liu, Chengqi Zhang, Bo Han

AAAI 2025 Federated Foundation Models on Heterogeneous Time Series Shengchao Chen, Guodong Long, Jing Jiang, Chengqi Zhang

TMLR 2025 Federated Generalized Novel Category Discovery with Prompts Tuning Lei Shen, Nan Pu, Zhun Zhong, Mingming Gong, Dianhai Yu, Chengqi Zhang, Bo Han

IJCAI 2025 Federated Low-Rank Adaptation for Foundation Models: A Survey Yiyuan Yang, Guodong Long, Qinghua Lu, Liming Zhu, Jing Jiang, Chengqi Zhang

AAAI 2025 Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach Zhiwei Li, Guodong Long, Tianyi Zhou, Jing Jiang, Chengqi Zhang

NeurIPS 2025 WALL-E: World Alignment by NeuroSymbolic Learning Improves World Model-Based LLM Agents Siyu Zhou, Tianyi Zhou, Yijun Yang, Guodong Long, Deheng Ye, Jing Jiang, Chengqi Zhang

NeurIPS 2024 ARC: A Generalist Graph Anomaly Detector with In-Context Learning Yixin Liu, Shiyuan Li, Yu Zheng, Qingfeng Chen, Chengqi Zhang, Shirui Pan

IJCAI 2024 Federated Prompt Learning for Weather Foundation Models on Devices Shengchao Chen, Guodong Long, Tao Shen, Jing Jiang, Chengqi Zhang

NeurIPS 2024 Mind the Gap Between Prototypes and Images in Cross-Domain Finetuning Hongduan Tian, Feng Liu, Zhanke Zhou, Tongliang Liu, Chengqi Zhang, Bo Han

ECML-PKDD 2024 Multivariate Traffic Demand Prediction via 2D Spectral Learning and Global Spatial Optimization Changlu Chen, Yanbin Liu, Ling Chen, Chengqi Zhang

NeurIPS 2024 Personalized Adapter for Large Meteorology Model on Devices: Towards Weather Foundation Models Shengchao Chen, Guodong Long, Jing Jiang, Chengqi Zhang

IJCAI 2024 What Hides Behind Unfairness? Exploring Dynamics Fairness in Reinforcement Learning Zhihong Deng, Jing Jiang, Guodong Long, Chengqi Zhang

TMLR 2023 Causal Reinforcement Learning: A Survey Zhihong Deng, Jing Jiang, Guodong Long, Chengqi Zhang

ICML 2023 Does Continual Learning Equally Forget All Parameters? Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang

IJCAI 2023 Dual Personalization on Federated Recommendation Chunxu Zhang, Guodong Long, Tianyi Zhou, Peng Yan, Zijian Zhang, Chengqi Zhang, Bo Yang

AAAI 2023 Federated Learning on Non-IID Graphs via Structural Knowledge Sharing Yue Tan, Yixin Liu, Guodong Long, Jing Jiang, Qinghua Lu, Chengqi Zhang

NeurIPS 2023 Structured Federated Learning Through Clustered Additive Modeling Jie Ma, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang

ECML-PKDD 2023 Voting from Nearest Tasks: Meta-Vote Pruning of Pre-Trained Models for Downstream Tasks Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang

ICML 2022 EAT-C: Environment-Adversarial Sub-Task Curriculum for Efficient Reinforcement Learning Shuang Ao, Tianyi Zhou, Jing Jiang, Guodong Long, Xuan Song, Chengqi Zhang

TMLR 2022 Extracting Local Reasoning Chains of Deep Neural Networks Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang

AAAI 2022 FedProto: Federated Prototype Learning Across Heterogeneous Clients Yue Tan, Guodong Long, Lu Liu, Tianyi Zhou, Qinghua Lu, Jing Jiang, Chengqi Zhang

ICMLW 2022 Vote for Nearest Neighbors Meta-Pruning of Self-Supervised Networks Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang

ICLR 2021 Isometric Propagation Network for Generalized Zero-Shot Learning Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Xuanyi Dong, Chengqi Zhang

AAAI 2020 Attribute Propagation Network for Graph Zero-Shot Learning Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang

NeurIPS 2020 Cooperative Heterogeneous Deep Reinforcement Learning Han Zheng, Pengfei Wei, Jing Jiang, Guodong Long, Qinghua Lu, Chengqi Zhang

NeurIPS 2020 Deep Reinforcement Learning with Stacked Hierarchical Attention for Text-Based Games Yunqiu Xu, Meng Fang, Ling Chen, Yali Du, Joey Tianyi Zhou, Chengqi Zhang

IJCAI 2020 Effective Search of Logical Forms for Weakly Supervised Knowledge-Based Question Answering Tao Shen, Xiubo Geng, Guodong Long, Jing Jiang, Chengqi Zhang, Daxin Jiang

IJCAI 2019 Attributed Graph Clustering: A Deep Attentional Embedding Approach Chun Wang, Shirui Pan, Ruiqi Hu, Guodong Long, Jing Jiang, Chengqi Zhang

IJCAI 2019 Graph WaveNet for Deep Spatial-Temporal Graph Modeling Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Chengqi Zhang

NeurIPS 2019 Learning to Propagate for Graph Meta-Learning Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang

IJCAI 2019 Prototype Propagation Networks (PPN) for Weakly-Supervised Few-Shot Learning on Category Graph Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Lina Yao, Chengqi Zhang

IJCAI 2018 Adversarially Regularized Graph Autoencoder for Graph Embedding Shirui Pan, Ruiqi Hu, Guodong Long, Jing Jiang, Lina Yao, Chengqi Zhang

ICLR 2018 Bi-Directional Block Self-Attention for Fast and Memory-Efficient Sequence Modeling Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang

AAAI 2018 DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Shirui Pan, Chengqi Zhang

IJCAI 2018 Efficient Attributed Network Embedding via Recursive Randomized Hashing Wei Wu, Bin Li, Ling Chen, Chengqi Zhang

IJCAI 2018 Reinforced Self-Attention Network: A Hybrid of Hard and Soft Attention for Sequence Modeling Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Sen Wang, Chengqi Zhang

IJCAI 2017 Recommendation vs Sentiment Analysis: A Text-Driven Latent Factor Model for Rating Prediction with Cold-Start Awareness Kaisong Song, Wei Gao, Shi Feng, Daling Wang, Kam-Fai Wong, Chengqi Zhang

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

AAAI 2016 Dynamic Concept Composition for Zero-Example Event Detection Xiaojun Chang, Yi Yang, Guodong Long, Chengqi Zhang, Alexander G. Hauptmann

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

IJCAI 2016 Unsupervised Feature Learning from Time Series Qin Zhang, Jia Wu, Hong Yang, Yingjie Tian, Chengqi Zhang

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

IJCAI 2015 Scalable Maximum Margin Matrix Factorization by Active Riemannian Subspace Search Yan Yan, Mingkui Tan, Ivor W. Tsang, Yi Yang, Chengqi Zhang, Qinfeng Shi

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

IJCAI 2011 Similarity-Based Approach for Positive and Unlabeled Learning Yanshan Xiao, Bo Liu, Jie Yin, Longbing Cao, Chengqi Zhang, Zhifeng Hao

ECML-PKDD 2009 Debt Detection in Social Security by Sequence Classification Using Both Positive and Negative Patterns Yanchang Zhao, Huaifeng Zhang, Shanshan Wu, Jian Pei, Longbing Cao, Chengqi Zhang, Hans Bohlscheid

AAAI 2007 Cost-Sensitive Imputing Missing Values with Ordering Xiaofeng Zhu, Shichao Zhang, Jilian Zhang, Chengqi Zhang

AAAI 2007 Measuring the Uncertainty of Differences for Contrasting Groups Jilian Zhang, Shichao Zhang, Xiaofeng Zhu, Xindong Wu, Chengqi Zhang

ICML 2002 Mining Both Positive and Negative Association Rules Xindong Wu, Chengqi Zhang, Shichao Zhang