He, Yi

24 publications

IJCAI 2025 A Novel Sparse Active Online Learning Framework for Fast and Accurate Streaming Anomaly Detection over Data Streams Zhong Chen, Yi He, Di Wu, Chen Zhao, Meikang Qiu

ICML 2025 Chaos Meets Attention: Transformers for Large-Scale Dynamical Prediction Yi He, Yiming Yang, Xiaoyuan Cheng, Hai Wang, Xiao Xue, Boli Chen, Yukun Hu

ICCV 2025 EmotiCrafter: Text-to-Emotional-Image Generation Based on Valence-Arousal Model Shengqi Dang, Yi He, Long Ling, Ziqing Qian, Nanxuan Zhao, Nan Cao

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

IJCAI 2025 How to Mitigate Information Loss in Knowledge Graphs for GraphRAG: Leveraging Triple Context Restoration and Query-Driven Feedback Manzong Huang, Chenyang Bu, Yi He, Xindong Wu

ICLR 2025 Learning Chaos in a Linear Way Xiaoyuan Cheng, Yi He, Yiming Yang, Xiao Xue, Sibo Cheng, Daniel Giles, Xiaohang Tang, Yukun Hu

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

TMLR 2025 Multi-Modal Foundation Models for Computational Pathology: A Survey Dong Li, Guihong Wan, Xintao Wu, Xinyu Wu, Xiaohui Chen, Yi He, Zhong Chen, Peter K Sorger, Chen Zhao

NeurIPS 2025 On the Sample Complexity of Differentially Private Policy Optimization Yi He, Xingyu Zhou

ICML 2025 Tensor-Var: Efficient Four-Dimensional Variational Data Assimilation Yiming Yang, Xiaoyuan Cheng, Daniel Giles, Sibo Cheng, Yi He, Xiao Xue, Boli Chen, Yukun Hu

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

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

AAAI 2024 MKG-FENN: A Multimodal Knowledge Graph Fused End-to-End Neural Network for Accurate Drug-Drug Interaction Prediction Di Wu, Wu Sun, Yi He, Zhong Chen, Xin Luo

AAAI 2023 Exploring Hypergraph of Earnings Call for Risk Prediction (Student Abstract) Yi He, Wenxin Tai, Fan Zhou, Yi Yang

ECML-PKDD 2023 MMA: Multi-Metric-Autoencoder for Analyzing High-Dimensional and Incomplete Data Cheng Liang, Di Wu, Yi He, Teng Huang, Zhong Chen, Xin Luo

AAAI 2023 Online Random Feature Forests for Learning in Varying Feature Spaces Christian Schreckenberger, Yi He, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt

AAAI 2023 Online Semi-Supervised Learning with Mix-Typed Streaming Features Di Wu, Shengda Zhuo, Yu Wang, Zhong Chen, Yi He

IJCAI 2023 Towards Utilitarian Online Learning - A Review of Online Algorithms in Open Feature Space Yi He, Christian Schreckenberger, Heiner Stuckenschmidt, Xindong Wu

IJCAI 2021 Interpretable Minority Synthesis for Imbalanced Classification Yi He, Fudong Lin, Xu Yuan, Nian-Feng Tzeng

AAAI 2021 Online Learning in Variable Feature Spaces Under Incomplete Supervision Yi He, Xu Yuan, Sheng Chen, Xindong Wu

ICCVW 2019 An Empirical Study of Detection-Based Video Instance Segmentation Qiang Wang, Yi He, Xiaoyun Yang, Zhao Yang, Philip H. S. Torr

IJCAI 2019 Online Learning from Capricious Data Streams: A Generative Approach Yi He, Baijun Wu, Di Wu, Ege Beyazit, Sheng Chen, Xindong Wu

IJCAI 2018 Toward Designing Convergent Deep Operator Splitting Methods for Task-Specific Nonconvex Optimization Risheng Liu, Shichao Cheng, Yi He, Xin Fan, Zhongxuan Luo