ask others

• Google
• Google Scholar
• Semantic Scholar
• Internet Archive Scholar
• CiteSeerX
• ORCID

• affiliation:College of William and Mary, School of Data Science, VA, USA
• affiliation (former):Old Dominion University, Department of Computer Science, VA, USA
• affiliation (Ph.D.):University of Louisiana at Lafayette, Center for Advanced Computer Studies (CACS), LA, USA

• Yi He —disambiguation page
• Yi He0001 — University of Texas at Dallas, Department of Computer Science, Richardson, TX, USA
• Yi He0002 —Max Planck Institute for Biological Cybernetics, Department of High-field Magnetic Resonance, Tübingen, Germany(and 1 more)
• Yi He0003 — University of Wisconsin-Madison, Teacher Education Building, WI, USA
• Yi He0004 — Huazhong University of Science and Technology, School of Automation, Wuhan, China
• Yi He0005 — Chinese Academy of Sciences, Wuhan Institute of Physics and Mathematics, China
• Yi He0006 — Chinese Academy of Sciences, Suzhou Institute of Biomedical Engineering and Technology, Jiangsu Key Laboratory of Medical Optics, China
• Yi He0008 — National University of Defense Technology, Computer School, Changsha, China
• Yi He0009 —Hainan University, School of Management, Haikou, Hainan, China(and 1 more)
• Yi He0010 — University of Chicago, IL, USA

• Yi He0011 — Nanjing University of Aeronautics and Astronautics, College of Automation Engineering, China
• Yi He0012 — Guangxi Vocational Normal University, Nanning, China
• Yi He0013 — Wuhan University of Technology, Intelligent Transportation Systems Research Center, China
• Yi He0014 — Northwest University, College of Urban and Environmental Sciences, Xi'an, China
• Yi He0015 — University of Michigan, Ann Arbor, MI, USA
• Yi He0016 —National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring, Lanzhou, China(and 1 more)
• Yi He0017 — Changsha University of Science and Technology, School of Computer and Communication Engineering, China
• Yi He0018 — Chengdu University of Information Technology, School of Computer, China
• Yi He0019 — Hainan University, School of Management, Haikou, China
• Yi He0020 —Wuhan University, Institute for Math & AI, China(and 1 more)
• Yi He0021 — Wuhan University, School of Information Management, China

• Shiang-Yi He
• Yi-Chao He
• Yi-Hai He(aka: Yihai He) — Beihang University, Beijing, China
• Yi-Xiao He
• Yi Jun He
• Yifan He(aka: YiFan He, Yi-Fan He) —disambiguation page
• Yizhou He(aka: Yi-zhou He, Yi-Zhou He) —disambiguation page
• Yihe Liu(aka: YiHe Liu, Yi He Liu) —disambiguation page
• He Yi
• He-Yi Zhang
• show all similar names

• 2026
• 
  [i15]
  Manzong Huang,Chenyang Bu,Yi He,Xingrui Zhuo,Xindong Wu:
  Relink: Constructing Query-Driven Evidence Graph On-the-Fly for GraphRAG.CoRRabs/2601.07192 (2026)
• 2025
• 
  [j23]
  Zhiqiang Wang,Sheri L. Barton,Jennifer H. Johnson,Yi He,Xingquan Zhu:
  Interpretable Individual Manatee Identification Using Sketch Images and Deep Neural Networks.IEEE Access13:218154-218168 (2025)
• 
  [j22]
  Shengda Zhuo,Di Wu,Yi He,Shuqiang Huang,Xindong Wu:
  Online Learning from Mix-typed, Drifted, and Incomplete Streaming Features.ACM Trans. Knowl. Discov. Data19(8):150:1-150:28 (2025)
• 
  [j21]
  Heng Lian,Yi He,Di Wu,Zhong Chen,Xingquan Zhu,Xindong Wu:
  Online Outlier Detection in Open Feature Spaces.IEEE Trans. Knowl. Data Eng.37(10):6091-6106 (2025)
• 
  [j20]
  Di Wu,Zechao Li,Zhikai Yu,Yi He,Xin Luo:
  Robust Low-Rank Latent Feature Analysis for Spatiotemporal Signal Recovery.IEEE Trans. Neural Networks Learn. Syst.36(2):2829-2842 (2025)
• 
  [c42]
  Heng Lian,Chen Zhao,Zhong Chen,Xingquan Zhu,My T. Thai,Yi He:
  Metric-Agnostic Continual Learning for Sustainable Group Fairness.AAAI2025:18648-18657
• 
  [c41]
  Chenyang Bu,Guojie Chang,Zihao Chen,CunYuan Dang,Zhize Wu,Yi He,Xindong Wu:
  Query-Driven Multimodal GraphRAG: Dynamic Local Knowledge Graph Construction for Online Reasoning.ACL (Findings)2025:21360-21380
• 
  [c40]
  Haoyang Jiang,Jindong Wang,Xingquan Zhu,Yi He:
  Topology-aware Neural Flux Prediction Guided by Physics.ICML2025
• 
  [c39]
  Jiajun Shen,Yufei Jin,Kaibu Feng,Yi He,Xingquan Zhu:
  HGEN: Heterogeneous Graph Ensemble Networks.IJCAI2025:6156-6163
• 
  [c38]
  Manzong Huang,Chenyang Bu,Yi He,Xindong Wu:
  How to Mitigate Information Loss in Knowledge Graphs for GraphRAG: Leveraging Triple Context Restoration and Query-Driven Feedback.IJCAI2025:8104-8112
• 
  [c37]
  Jian Wu,Sarah Rajtmajer,Yian Yin,Yi He,Stasa Milojevic:
  The 2nd International Workshop on Artificial Intelligence for the Science of Science.JCDL2025:355-357
• 
  [c36]
  Zhong Chen,Yi He,Di Wu,Wenbin Zhang,Zhiqiang Deng:
  ℓ_{1, ∞} Mixed Norm Promoted Row Sparsity for Fast Online CUR Decomposition Learning in Varying Feature Spaces.SDM2025:124-133
• 
  [i14]
  Manzong Huang,Chenyang Bu,Yi He,Xindong Wu:
  How to Mitigate Information Loss in Knowledge Graphs for GraphRAG: Leveraging Triple Context Restoration and Query-Driven Feedback.CoRRabs/2501.15378 (2025)
• 
  [i13]
  Jiaxi Yang,Mengqi Zhang,Yiqiao Jin,Hao Chen,Qingsong Wen,Lu Lin,Yi He,Weijie Xu,James Evans,Jindong Wang:
  Topological Structure Learning Should Be A Research Priority for LLM-Based Multi-Agent Systems.CoRRabs/2505.22467 (2025)
• 
  [i12]
  Haoyang Jiang,Jindong Wang,Xingquan Zhu,Yi He:
  Topology-aware Neural Flux Prediction Guided by Physics.CoRRabs/2506.05676 (2025)
• 
  [i11]
  Shengda Zhuo,Di Wu,Yi He,Shuqiang Huang,Xindong Wu:
  Extension OL-MDISF: Online Learning from Mix-Typed, Drifted, and Incomplete Streaming Features.CoRRabs/2507.10594 (2025)
• 
  [i10]
  Jiajun Shen,Yufei Jin,Yi He,Xingquan Zhu:
  HGEN: Heterogeneous Graph Ensemble Networks.CoRRabs/2509.09843 (2025)
• 
  [i9]
  Jiajun Shen,Yufei Jin,Yi He,Xingquan Zhu:
  LHGEL: Large Heterogeneous Graph Ensemble Learning using Batch View Aggregation.CoRRabs/2510.03432 (2025)
• 2024
• 
  [j19]
  Song Deng,Qianliang Li,Renjie Dai,Siming Wei,Di Wu,Yi He,Xindong Wu:
  A Chinese power text classification algorithm based on deep active learning.Appl. Soft Comput.150:111067 (2024)
• 
  [j18]
  Jie Yang,Zhijun Wang,Guoyin Wang,Yanmin Liu,Yi He,Di Wu:
  OSFS-Vague: Online streaming feature selection algorithm based on vague set.CAAI Trans. Intell. Technol.9(6):1451-1466 (2024)
• 
  [j17]
  Teng Huang,Cheng Liang,Di Wu,Yi He:
  A Debiasing Autoencoder for Recommender System.IEEE Trans. Consumer Electron.70(1):3603-3613 (2024)
• 
  [j16]
  Heng Lian,Di Wu,Bo-Jian Hou,Jian Wu,Yi He:
  Online Learning From Evolving Feature Spaces With Deep Variational Models.IEEE Trans. Knowl. Data Eng.36(8):4144-4162 (2024)
• 
  [j15]
  Di Wu,Xin Luo,Yi He,Mengchu Zhou:
  A Prediction-Sampling-Based Multilayer-Structured Latent Factor Model for Accurate Representation to High-Dimensional and Sparse Data.IEEE Trans. Neural Networks Learn. Syst.35(3):3845-3858 (2024)
• 
  [j14]
  Di Wu,Peng Zhang,Yi He,Xin Luo:
  MMLF: Multi-Metric Latent Feature Analysis for High-Dimensional and Incomplete Data.IEEE Trans. Serv. Comput.17(2):575-588 (2024)
• 
  [c35]
  Di Wu,Wu Sun,Yi He,Zhong Chen,Xin Luo:
  MKG-FENN: A Multimodal Knowledge Graph Fused End-to-End Neural Network for Accurate Drug-Drug Interaction Prediction.AAAI2024:10216-10224
• 
  [c34]
  Yufei Jin,Richard Gao,Yi He,Xingquan Zhu:
  GLDL: Graph Label Distribution Learning.AAAI2024:12965-12974
• 
  [c33]
  Zhong Chen,Yi He,Di Wu,Liudong Zuo,Keren Li,Wenbin Zhang,Zhiqiang Deng:
  ℓ1, 2-Norm and CUR Decomposition based Sparse Online Active Learning for Data Streams with Streaming Features.IEEE Big Data2024:384-393
• 
  [c32]
  Mohammad Wahiduzzaman Khan,Sheng Chen,Yi He:
  Learning Gradual Typing Performance.ECOOP2024:21:1-21:27
• 
  [c31]
  Heng Lian,Yi He:
  Urban Functional Zone Delineation Aided by Vision Foundation Models.ICDM (Workshops)2024:40-43
• 
  [c30]
  Heng Lian,Yu Huang,Xingquan Zhu,Yi He:
  Utilitarian Online Learning from Open-World Soft Sensing.ICDM2024:241-250
• 
  [c29]
  Yufei Jin,Heng Lian,Yi He,Xingquan Zhu:
  HGDL: Heterogeneous Graph Label Distribution Learning.NeurIPS2024
• 
  [c28]
  Zhong Chen,Yi He,Di Wu,Huixin Zhan,Victor S. Sheng,Kun Zhang:
  Robust Sparse Online Learning for Data Streams with Streaming Features.SDM2024:181-189
• 
  [i8]
  Kehinde Ajayi,Leizhen Zhang,Yi He,Jian Wu:
  Uncertainty Quantification in Table Structure Recognition.CoRRabs/2407.01731 (2024)
• 
  [i7]
  Leizhen Zhang,Lusi Li,Di Wu,Sheng Chen,Yi He:
  Fairness-Aware Streaming Feature Selection with Causal Graphs.CoRRabs/2408.12665 (2024)
• 
  [i6]
  Fulai Yang,Di Wu,Yi He,Li Tao,Xin Luo:
  End-to-end Graph Learning Approach for Cognitive Diagnosis of Student Tutorial.CoRRabs/2411.00845 (2024)
• 2023
• 
  [j13]
  Song Deng,Qicong Hu,Di Wu,Yi He:
  BCTC-KSM: A blockchain-assisted threshold cryptography for key security management in power IoT data sharing.Comput. Electr. Eng.108:108666 (2023)
• 
  [j12]
  Di Wu,Yi He,Xin Luo:
  A Graph-Incorporated Latent Factor Analysis Model for High-Dimensional and Sparse Data.IEEE Trans. Emerg. Top. Comput.11(4):907-917 (2023)
• 
  [j11]
  Song Deng,Jiantang Zhang,Di Wu,Yi He,Xiangpeng Xie,Xindong Wu:
  A Quantitative Risk Assessment Model for Distribution Cyber-Physical System Under Cyberattack.IEEE Trans. Ind. Informatics19(3):2899-2908 (2023)
• 
  [j10]
  Zijie Pan,Li Hu,Weixuan Tang,Jin Li,Yi He,Zheli Liu:
  Privacy-Preserving Multi-Granular Federated Neural Architecture Search - A General Framework.IEEE Trans. Knowl. Data Eng.35(3):2975-2986 (2023)
• 
  [j9]
  Di Wu,Peng Zhang,Yi He,Xin Luo:
  A Double-Space and Double-Norm Ensembled Latent Factor Model for Highly Accurate Web Service QoS Prediction.IEEE Trans. Serv. Comput.16(2):802-814 (2023)
• 
  [j8]
  Song Deng,Yujia Zhai,Di Wu,Dong Yue,Xiong Fu,Yi He:
  A Lightweight Dynamic Storage Algorithm With Adaptive Encoding for Energy Internet.IEEE Trans. Serv. Comput.16(5):3115-3128 (2023)
• 
  [c27]
  Christian Schreckenberger,Yi He,Stefan Lüdtke,Christian Bartelt,Heiner Stuckenschmidt:
  Online Random Feature Forests for Learning in Varying Feature Spaces.AAAI2023:4587-4595
• 
  [c26]
  Di Wu,Shengda Zhuo,Yu Wang,Zhong Chen,Yi He:
  Online Semi-supervised Learning with Mix-Typed Streaming Features.AAAI2023:4720-4728
• 
  [c25]
  Lusi Li,Jie Li,Yi He,Laura Slayton:
  A Domain Adaptation-based Detector for Cooperative Spectrum Sensing.CCNC2023:680-681
• 
  [c24]
  Xiaoyu Zhu,Chenyang Bu,Bingbing Dong,Shengwei Ji,Yi He,Xindong Wu:
  IKGN: Intention-aware Knowledge Graph Network for POI Recommendation.ICDM2023:908-917
• 
  [c23]
  Yi He,Christian Schreckenberger,Heiner Stuckenschmidt,Xindong Wu:
  Towards Utilitarian Online Learning - A Review of Online Algorithms in Open Feature Space.IJCAI2023:6647-6655
• 
  [c22]
  Cheng Liang,Di Wu,Yi He,Teng Huang,Zhong Chen,Xin Luo:
  MMA: Multi-Metric-Autoencoder for Analyzing High-Dimensional and Incomplete Data.ECML/PKDD (5)2023:3-19
• 
  [e1]
  Jihe Wang,Yi He,Thang N. Dinh,Christan Grant,Meikang Qiu,Witold Pedrycz:
  IEEE International Conference on Data Mining, ICDM 2023 - Workshops, Shanghai, China, December 4, 2023.IEEE2023, ISBN979-8-3503-8164-1[contents]
• 2022
• 
  [j7]
  Song Deng,Fulin Chen,Di Wu,Yi He,Hui Ge,Yuan Ge:
  Quantitative combination load forecasting model based on forecasting error optimization.Comput. Electr. Eng.101:108125 (2022)
• 
  [j6]
  Di Wu,Xin Luo,Mingsheng Shang,Yi He,Guoyin Wang,Xindong Wu:
  A Data-Characteristic-Aware Latent Factor Model for Web Services QoS Prediction.IEEE Trans. Knowl. Data Eng.34(6):2525-2538 (2022)
• 
  [j5]
  Di Wu,Qiang He,Xin Luo,Mingsheng Shang,Yi He,Guoyin Wang:
  A Posterior-Neighborhood-Regularized Latent Factor Model for Highly Accurate Web Service QoS Prediction.IEEE Trans. Serv. Comput.15(2):793-805 (2022)
• 
  [j4]
  Di Wu,Yi He,Xin Luo,MengChu Zhou:
  A Latent Factor Analysis-Based Approach to Online Sparse Streaming Feature Selection.IEEE Trans. Syst. Man Cybern. Syst.52(11):6744-6758 (2022)
• 
  [c21]
  Bo Sun,Di Wu,Mingsheng Shang,Yi He:
  Toward Auto-Learning Hyperparameters for Deep Learning-Based Recommender Systems.DASFAA (2)2022:323-331
• 
  [c20]
  Zhikai Yu,Di Wu,Yi He:
  A Robust Latent Factor Analysis Model for Incomplete Data Recovery in Wireless Sensor Networks.EDGE2022:178-183
• 
  [c19]
  Feilong Chen,Di Wu,Jie Yang,Yi He:
  Online Sparse Streaming Feature Selection with Uncertainty.ICNSC2022:1-6
• 
  [c18]
  Chao Jiang,Yi He,Richard Chapman,Hongyi Wu:
  Camouflaged Poisoning Attack on Graph Neural Networks.ICMR2022:451-461
• 
  [c17]
  Heng Lian,John Scovil Atwood,Bojian Hou,Jian Wu,Yi He:
  Online Deep Learning from Doubly-Streaming Data.ACM Multimedia2022:3185-3194
• 
  [c16]
  Cheng Liang,Yi He,Teng Huang,Di Wu:
  AutoRec++: Incorporating Debias Methods into Autoencoder-based Recommender System.SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta2022:1876-1881
• 
  [c15]
  Yuanpeng Hu,Xianmin Wang,Cheng Liang,Jing Li,Di Wu,Yi He:
  OR-AutoRec: An Outlier-Resilient Autoencoder-based Recommendation model.SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta2022:1918-1923
• 
  [i5]
  Di Wu,Yi He,Xin Luo:
  Graph-incorporated Latent Factor Analysis for High-dimensional and Sparse Matrices.CoRRabs/2204.07818 (2022)
• 
  [i4]
  Di Wu,Peng Zhang,Yi He,Xin Luo:
  A Multi-Metric Latent Factor Model for Analyzing High-Dimensional and Sparse data.CoRRabs/2204.07819 (2022)
• 
  [i3]
  Heng Lian,John Scovil Atwood,Bojian Hou,Jian Wu,Yi He:
  Online Deep Learning from Doubly-Streaming Data.CoRRabs/2204.11793 (2022)
• 
  [i2]
  Feilong Chen,Di Wu,Jie Yang,Yi He:
  An Online Sparse Streaming Feature Selection Algorithm.CoRRabs/2208.01562 (2022)
• 
  [i1]
  Cheng Liang,Teng Huang,Yi He,Song Deng,Di Wu,Xin Luo:
  Multi-Metric AutoRec for High Dimensional and Sparse User Behavior Data Prediction.CoRRabs/2212.13879 (2022)
• 2021
• 
  [j3]
  Yi He,Baijun Wu,Di Wu,Ege Beyazit,Sheng Chen,Xindong Wu:
  Toward Mining Capricious Data Streams: A Generative Approach.IEEE Trans. Neural Networks Learn. Syst.32(3):1228-1240 (2021)
• 
  [j2]
  Di Wu,Xin Luo,Mingsheng Shang,Yi He,Guoyin Wang,MengChu Zhou:
  A Deep Latent Factor Model for High-Dimensional and Sparse Matrices in Recommender Systems.IEEE Trans. Syst. Man Cybern. Syst.51(7):4285-4296 (2021)
• 
  [c14]
  Yi He,Xu Yuan,Sheng Chen,Xindong Wu:
  Online Learning in Variable Feature Spaces under Incomplete Supervision.AAAI2021:4106-4114
• 
  [c13]
  Peng Zhang,Yi He,Di Wu:
  An Ensemble Latent Factor Model for Highly Accurate Web Service QoS Prediction.ICBK2021:361-368
• 
  [c12]
  Yi He,Jiaxian Dong,Bo-Jian Hou,Yu Wang,Fei Wang:
  Online Learning in Variable Feature Spaces with Mixed Data.ICDM2021:181-190
• 
  [c11]
  Yi He,Fudong Lin,Xu Yuan,Nian-Feng Tzeng:
  Interpretable Minority Synthesis for Imbalanced Classification.IJCAI2021:2542-2548
• 
  [c10]
  Yi He,Sheng Chen,Baijun Wu,Xu Yuan,Xindong Wu:
  Unsupervised Lifelong Learning with Curricula.WWW2021:3534-3545
• 2020
• 
  [c9]
  Ege Beyazit,Yi He,Nian-Feng Tzeng,Xindong Wu:
  Online Learning to Accelerate Neural Network Inference with Traveling Classifiers.ECAI2020:1016-1023
• 
  [c8]
  Yi He,Baijun Wu,Di Wu,Xindong Wu:
  On Partial Multi-Task Learning.ECAI2020:1174-1181
• 
  [c7]
  Yi He,Xu Yuan,Nian-Feng Tzeng,Xindong Wu:
  Active Learning with Multi-Granular Graph Auto-Encoder.ICDM2020:1058-1063
• 
  [c6]
  Jing Chen,Yi He,Vijay Raghavan:
  Learning with Partial Multi-Outlooks.IJCNN2020:1-8
• 
  [c5]
  Yi He,Sheng Chen,Thu Nguyen,Bruce A. Wade,Xindong Wu:
  Deep Matrix Tri-Factorization: Mining Vertex-wise Interactions in Multi-Space Attributed Graphs.SDM2020:334-342

• 2019
• 
  [j1]
  Baijun Wu,John Peter Campora III,Yi He,Alexander Schlecht,Sheng Chen:
  Generating precise error specifications for C: a zero shot learning approach.Proc. ACM Program. Lang.3(OOPSLA):160:1-160:30 (2019)
• 
  [c4]
  Di Wu,Yi He,Xin Luo,Mingsheng Shang,Xindong Wu:
  Online Feature Selection with Capricious Streaming Features: A General Framework.IEEE BigData2019:683-688
• 
  [c3]
  Yi He,Baijun Wu,Di Wu,Ege Beyazit,Sheng Chen,Xindong Wu:
  Online Learning from Capricious Data Streams: A Generative Approach.IJCAI2019:2491-2497
• 
  [c2]
  Di Wu,Xin Luo,Mingsheng Shang,Yi He,Guoyin Wang,Xindong Wu:
  A Data-Aware Latent Factor Model for Web Service QoS Prediction.PAKDD (1)2019:384-399
• 2018
• 
  [c1]
  Yi He,Di Wu,Ege Beyazit,Xiaoduan Sun,Xindong Wu:
  Supervised Data Synthesizing and Evolving - A Framework for Real-World Traffic Crash Severity Classification.ICTAI2018:163-170

manage site settings