Yi He

According to our database, Yi He authored at least 44 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Prediction-Sampling-Based Multilayer-Structured Latent Factor Model for Accurate Representation to High-Dimensional and Sparse Data.

Di Wu, Xin Luo, Yi He, Mengchu Zhou

IEEE Trans. Neural Networks Learn. Syst., March, 2024

A Chinese power text classification algorithm based on deep active learning.

Song Deng, Qianliang Li, Renjie Dai, Siming Wei, Di Wu, Yi He, Xindong Wu

Appl. Soft Comput., January, 2024

MMLF: Multi-Metric Latent Feature Analysis for High-Dimensional and Incomplete Data.

Di Wu, Peng Zhang, Yi He, Xin Luo

IEEE Trans. Serv. Comput., 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

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

BCTC-KSM: A blockchain-assisted threshold cryptography for key security management in power IoT data sharing.

Song Deng, Qicong Hu, Di Wu, Yi He

Comput. Electr. Eng., May, 2023

Privacy-Preserving Multi-Granular Federated Neural Architecture Search - A General Framework.

Zijie Pan, Li Hu, Weixuan Tang, Jin Li, Yi He, Zheli Liu

IEEE Trans. Knowl. Data Eng., March, 2023

A Quantitative Risk Assessment Model for Distribution Cyber-Physical System Under Cyberattack.

Song Deng, Jiantang Zhang, Di Wu, Yi He, Xiangpeng Xie, Xindong Wu

IEEE Trans. Ind. Informatics, March, 2023

A Double-Space and Double-Norm Ensembled Latent Factor Model for Highly Accurate Web Service QoS Prediction.

Di Wu, Peng Zhang, Yi He, Xin Luo

IEEE Trans. Serv. Comput., 2023

A Lightweight Dynamic Storage Algorithm With Adaptive Encoding for Energy Internet.

Song Deng, Yujia Zhai, Di Wu, Dong Yue, Xiong Fu, Yi He

IEEE Trans. Serv. Comput., 2023

A Graph-Incorporated Latent Factor Analysis Model for High-Dimensional and Sparse Data.

Di Wu, Yi He, Xin Luo

IEEE Trans. Emerg. Top. Comput., 2023

MMA: Multi-Metric-Autoencoder for Analyzing High-Dimensional and Incomplete Data.

Cheng Liang, Di Wu, Yi He, Teng Huang, Zhong Chen, Xin Luo

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

A Domain Adaptation-based Detector for Cooperative Spectrum Sensing.

Lusi Li, Jie Li, Yi He, Laura Slayton

Proceedings of the 20th IEEE Consumer Communications & Networking Conference, 2023

Online Semi-supervised Learning with Mix-Typed Streaming Features.

Di Wu, Shengda Zhuo, Yu Wang, Zhong Chen, Yi He

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

A Latent Factor Analysis-Based Approach to Online Sparse Streaming Feature Selection.

Di Wu, Yi He, Xin Luo, MengChu Zhou

IEEE Trans. Syst. Man Cybern. Syst., 2022

A Posterior-Neighborhood-Regularized Latent Factor Model for Highly Accurate Web Service QoS Prediction.

Di Wu, Qiang He, Xin Luo, Mingsheng Shang, Yi He, Guoyin Wang

IEEE Trans. Serv. Comput., 2022

A Data-Characteristic-Aware Latent Factor Model for Web Services QoS Prediction.

Di Wu, Xin Luo, Mingsheng Shang, Yi He, Guoyin Wang, Xindong Wu

IEEE Trans. Knowl. Data Eng., 2022

Multi-Metric AutoRec for High Dimensional and Sparse User Behavior Data Prediction.

Cheng Liang, Teng Huang, Yi He, Song Deng, Di Wu, Xin Luo

CoRR, 2022

An Online Sparse Streaming Feature Selection Algorithm.

Feilong Chen, Di Wu, Jie Yang, Yi He

CoRR, 2022

A Multi-Metric Latent Factor Model for Analyzing High-Dimensional and Sparse data.

Di Wu, Peng Zhang, Yi He, Xin Luo

CoRR, 2022

Graph-incorporated Latent Factor Analysis for High-dimensional and Sparse Matrices.

Di Wu, Yi He, Xin Luo

CoRR, 2022

Quantitative combination load forecasting model based on forecasting error optimization.

Song Deng, Fulin Chen, Di Wu, Yi He, Hui Ge, Yuan Ge

Comput. Electr. Eng., 2022

AutoRec++: Incorporating Debias Methods into Autoencoder-based Recommender System.

Cheng Liang, Yi He, Teng Huang, Di Wu

Proceedings of the IEEE Smartworld, 2022

OR-AutoRec: An Outlier-Resilient Autoencoder-based Recommendation model.

Yuanpeng Hu, Xianmin Wang, Cheng Liang, Jing Li, Di Wu, Yi He

Proceedings of the IEEE Smartworld, 2022

Camouflaged Poisoning Attack on Graph Neural Networks.

Chao Jiang, Yi He, Richard Chapman, Hongyi Wu

Proceedings of the ICMR '22: International Conference on Multimedia Retrieval, Newark, NJ, USA, June 27, 2022

Online Sparse Streaming Feature Selection with Uncertainty.

Feilong Chen, Di Wu, Jie Yang, Yi He

Proceedings of the IEEE International Conference on Networking, Sensing and Control, 2022

A Robust Latent Factor Analysis Model for Incomplete Data Recovery in Wireless Sensor Networks.

Zhikai Yu, Di Wu, Yi He

Proceedings of the IEEE International Conference on Edge Computing and Communications, 2022

Toward Auto-Learning Hyperparameters for Deep Learning-Based Recommender Systems.

Bo Sun, Di Wu, Mingsheng Shang, Yi He

Proceedings of the Database Systems for Advanced Applications, 2022

2021

A Deep Latent Factor Model for High-Dimensional and Sparse Matrices in Recommender Systems.

Di Wu, Xin Luo, Mingsheng Shang, Yi He, Guoyin Wang, MengChu Zhou

IEEE Trans. Syst. Man Cybern. Syst., 2021

Toward Mining Capricious Data Streams: A Generative Approach.

Yi He, Baijun Wu, Di Wu, Ege Beyazit, Sheng Chen, Xindong Wu

IEEE Trans. Neural Networks Learn. Syst., 2021

Unsupervised Lifelong Learning with Curricula.

Yi He, Sheng Chen, Baijun Wu, Xu Yuan, Xindong Wu

Proceedings of the WWW '21: The Web Conference 2021, 2021

Interpretable Minority Synthesis for Imbalanced Classification.

Yi He, Fudong Lin, Xu Yuan, Nian-Feng Tzeng

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Online Learning in Variable Feature Spaces with Mixed Data.

Yi He, Jiaxian Dong, Bo-Jian Hou, Yu Wang, Fei Wang

Proceedings of the IEEE International Conference on Data Mining, 2021

An Ensemble Latent Factor Model for Highly Accurate Web Service QoS Prediction.

Peng Zhang, Yi He, Di Wu

Proceedings of the 2021 IEEE International Conference on Big Knowledge, 2021

Online Learning in Variable Feature Spaces under Incomplete Supervision.

Yi He, Xu Yuan, Sheng Chen, Xindong Wu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Deep Matrix Tri-Factorization: Mining Vertex-wise Interactions in Multi-Space Attributed Graphs.

Yi He, Sheng Chen, Thu Nguyen, Bruce A. Wade, Xindong Wu

Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

Learning with Partial Multi-Outlooks.

Jing Chen, Yi He, Vijay Raghavan

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Active Learning with Multi-Granular Graph Auto-Encoder.

Yi He, Xu Yuan, Nian-Feng Tzeng, Xindong Wu

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Online Learning to Accelerate Neural Network Inference with Traveling Classifiers.

Ege Beyazit, Yi He, Nian-Feng Tzeng, Xindong Wu

Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

On Partial Multi-Task Learning.

Yi He, Baijun Wu, Di Wu, Xindong Wu

Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

2019

Generating precise error specifications for C: a zero shot learning approach.

Baijun Wu, John Peter Campora III, Yi He, Alexander Schlecht, Sheng Chen

Proc. ACM Program. Lang., 2019

A Data-Aware Latent Factor Model for Web Service QoS Prediction.

Di Wu, Xin Luo, Mingsheng Shang, Yi He, Guoyin Wang, Xindong Wu

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

Online Learning from Capricious Data Streams: A Generative Approach.

Yi He, Baijun Wu, Di Wu, Ege Beyazit, Sheng Chen, Xindong Wu

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Online Feature Selection with Capricious Streaming Features: A General Framework.

Di Wu, Yi He, Xin Luo, Mingsheng Shang, Xindong Wu

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Supervised Data Synthesizing and Evolving - A Framework for Real-World Traffic Crash Severity Classification.

Yi He, Di Wu, Ege Beyazit, Xiaoduan Sun, Xindong Wu

Proceedings of the IEEE 30th International Conference on Tools with Artificial Intelligence, 2018