Publications
Preprint
Conference
Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning [PDF] [Code]
Yue Tan, Chen Chen, Weiming Zhuang, Xin Dong, Lingjuan Lyu, Guodong Long.
Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023.
A short version has been accepted to SIGKDD Workshop on FL4Data-Mining, 2023.Federated Learning on Non-IID Graphs via Structural Knowledge Sharing [PDF] [Code]
Yue Tan, Yixin Liu, Guodong Long, Jing Jiang, Qinghua Lu, Chengqi Zhang.
AAAI Conference on Artificial Intelligence (AAAI), 2023. (Oral)Federated Learning from Pre-Trained Models: A Contrastive Learning Approach [PDF] [Code]
Yue Tan, Guodong Long, Jie Ma, Lu Liu, Tianyi Zhou, Jing Jiang.
Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022. (Spotlight)
A short version has been accepted to ICML Workshop on Pre-training, 2022.FedProto: Federated Prototype Learning across Heterogeneous Clients [PDF] [Code]
Yue Tan, Guodong Long, Lu Liu, Tianyi Zhou, Qinghua Lu, Jing Jiang, Chengqi Zhang.
AAAI Conference on Artificial Intelligence (AAAI), 2022. (15% acceptance rate)An In-Vehicle Keyword Spotting System with Multi-Source Fusion for Vehicle Applications [PDF]
Yue Tan, Kan Zheng, Lei Lei.
IEEE Wireless Communications and Networking Conference (WCNC), 2019.
Journal
LSTM-Based Anomaly Detection for Non-Linear Dynamical System [PDF]
Yue Tan, Chunjing Hu, Kuan Zhang, Kan Zheng, Ethan A Davis, Jae Sung Park.
IEEE Access, 2020.Dynamic Energy Dispatch Based on Deep Reinforcement Learning in IoT-Driven Smart Isolated Microgrids [PDF]
Lei Lei, Yue Tan, Glenn Dahlenburg, Wei Xiang, Kan Zheng.
IEEE Internet of Things Journal, 2020. (IF: 9.94)Deep Reinforcement Learning for Autonomous Internet of Things: Model, Applications and Challenges [PDF]
Lei Lei, Yue Tan, Kan Zheng, Shiwen Liu, Kuan Zhang, Xuemin Shen.
IEEE Communications Surveys & Tutorials, 2020. (Top-1 Journal in IEEE, IF: 25.25)
Book Chapter
Federated Learning for Open Banking [LINK]
Guodong Long, Yue Tan, Jing Jiang, Chengqi Zhang.
Federated Learning - Privacy and Incentive, Editored by Prof. Qiang Yang, Springer, 2020.Federated Learning for Privacy-Preserving Open Innovation Future on Digital Health [LINK]
Guodong Long, Tao Shen, Yue Tan, Leah Gerrard, Allison Clarke, Jing Jiang.
Humanity Driven AI, Springer, 2021.