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Yi He 0007
Person information
- 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
Other persons with the same name
- Yi He — disambiguation page
- Yi He 0001 — University of Texas at Dallas, Department of Computer Science, Richardson, TX, USA
- Yi He 0002
— Max Planck Institute for Biological Cybernetics, Department of High-field Magnetic Resonance, Tübingen, Germany (and 1 more)
- Yi He 0003
— University of Wisconsin-Madison, Teacher Education Building, WI, USA
- Yi He 0004
— Huazhong University of Science and Technology, School of Automation, Wuhan, China
- Yi He 0005
— Chinese Academy of Sciences, Wuhan Institute of Physics and Mathematics, China
- Yi He 0006
— Chinese Academy of Sciences, Suzhou Institute of Biomedical Engineering and Technology, Jiangsu Key Laboratory of Medical Optics, China
- Yi He 0008 — National University of Defense Technology, Computer School, Changsha, China
- Yi He 0009 — Hainan University, School of Management, Haikou, Hainan, China (and 1 more)
- Yi He 0010
— University of Chicago, IL, USA
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Journal Articles
- 2024
- [j17]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) - [j16]Teng Huang
, Cheng Liang
, Di Wu
, Yi He
:
A Debiasing Autoencoder for Recommender System. IEEE Trans. Consumer Electron. 70(1): 3603-3613 (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) - 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. Informatics 19(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) - 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) - 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) - 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)
Conference and Workshop Papers
- 2024
- [c29]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. AAAI 2024: 10216-10224 - [c28]Yufei Jin, Richard Gao, Yi He
, Xingquan Zhu:
GLDL: Graph Label Distribution Learning. AAAI 2024: 12965-12974 - [c27]Zhong Chen, Yi He
, Di Wu, Huixin Zhan, Victor S. Sheng, Kun Zhang:
Robust Sparse Online Learning for Data Streams with Streaming Features. SDM 2024: 181-189 - 2023
- [c26]Christian Schreckenberger
, Yi He
, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
:
Online Random Feature Forests for Learning in Varying Feature Spaces. AAAI 2023: 4587-4595 - [c25]Di Wu, Shengda Zhuo, Yu Wang
, Zhong Chen
, Yi He
:
Online Semi-supervised Learning with Mix-Typed Streaming Features. AAAI 2023: 4720-4728 - [c24]Lusi Li
, Jie Li, Yi He, Laura Slayton:
A Domain Adaptation-based Detector for Cooperative Spectrum Sensing. CCNC 2023: 680-681 - [c23]Xiaoyu Zhu, Chenyang Bu, Bingbing Dong, Shengwei Ji, Yi He
, Xindong Wu:
IKGN: Intention-aware Knowledge Graph Network for POI Recommendation. ICDM 2023: 908-917 - [c22]Yi He
, Christian Schreckenberger
, Heiner Stuckenschmidt
, Xindong Wu:
Towards Utilitarian Online Learning - A Review of Online Algorithms in Open Feature Space. IJCAI 2023: 6647-6655 - [c21]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 - 2022
- [c20]Bo Sun, Di Wu, Mingsheng Shang, Yi He:
Toward Auto-Learning Hyperparameters for Deep Learning-Based Recommender Systems. DASFAA (2) 2022: 323-331 - [c19]Zhikai Yu, Di Wu
, Yi He:
A Robust Latent Factor Analysis Model for Incomplete Data Recovery in Wireless Sensor Networks. EDGE 2022: 178-183 - [c18]Feilong Chen, Di Wu, Jie Yang, Yi He:
Online Sparse Streaming Feature Selection with Uncertainty. ICNSC 2022: 1-6 - [c17]Chao Jiang, Yi He
, Richard Chapman, Hongyi Wu:
Camouflaged Poisoning Attack on Graph Neural Networks. ICMR 2022: 451-461 - [c16]Cheng Liang, Yi He, Teng Huang, Di Wu:
AutoRec++: Incorporating Debias Methods into Autoencoder-based Recommender System. SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta 2022: 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/Meta 2022: 1918-1923 - 2021
- [c14]Yi He
, Xu Yuan
, Sheng Chen, Xindong Wu:
Online Learning in Variable Feature Spaces under Incomplete Supervision. AAAI 2021: 4106-4114 - [c13]Peng Zhang, Yi He
, Di Wu:
An Ensemble Latent Factor Model for Highly Accurate Web Service QoS Prediction. ICBK 2021: 361-368 - [c12]Yi He
, Jiaxian Dong, Bo-Jian Hou, Yu Wang, Fei Wang:
Online Learning in Variable Feature Spaces with Mixed Data. ICDM 2021: 181-190 - [c11]Yi He
, Fudong Lin, Xu Yuan
, Nian-Feng Tzeng:
Interpretable Minority Synthesis for Imbalanced Classification. IJCAI 2021: 2542-2548 - [c10]Yi He
, Sheng Chen, Baijun Wu, Xu Yuan
, Xindong Wu:
Unsupervised Lifelong Learning with Curricula. WWW 2021: 3534-3545 - 2020
- [c9]Ege Beyazit, Yi He, Nian-Feng Tzeng, Xindong Wu:
Online Learning to Accelerate Neural Network Inference with Traveling Classifiers. ECAI 2020: 1016-1023 - [c8]Yi He, Baijun Wu, Di Wu
, Xindong Wu:
On Partial Multi-Task Learning. ECAI 2020: 1174-1181 - [c7]Yi He
, Xu Yuan
, Nian-Feng Tzeng, Xindong Wu:
Active Learning with Multi-Granular Graph Auto-Encoder. ICDM 2020: 1058-1063 - [c6]Jing Chen, Yi He
, Vijay Raghavan:
Learning with Partial Multi-Outlooks. IJCNN 2020: 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. SDM 2020: 334-342 - 2019
- [c4]Di Wu, Yi He
, Xin Luo, Mingsheng Shang, Xindong Wu:
Online Feature Selection with Capricious Streaming Features: A General Framework. IEEE BigData 2019: 683-688 - [c3]Yi He
, Baijun Wu, Di Wu, Ege Beyazit, Sheng Chen, Xindong Wu:
Online Learning from Capricious Data Streams: A Generative Approach. IJCAI 2019: 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. ICTAI 2018: 163-170
Editorship
- 2023
- [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. IEEE 2023, ISBN 979-8-3503-8164-1 [contents]
Informal and Other Publications
- 2022
- [i4]Di Wu, Yi He, Xin Luo:
Graph-incorporated Latent Factor Analysis for High-dimensional and Sparse Matrices. CoRR abs/2204.07818 (2022) - [i3]Di Wu, Peng Zhang, Yi He, Xin Luo:
A Multi-Metric Latent Factor Model for Analyzing High-Dimensional and Sparse data. CoRR abs/2204.07819 (2022) - [i2]Feilong Chen, Di Wu, Jie Yang, Yi He:
An Online Sparse Streaming Feature Selection Algorithm. CoRR abs/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. CoRR abs/2212.13879 (2022)
Coauthor Index
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