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Yue Tan
Yue Tan
Australian AI Institute, University of Technology Sydney
Bestätigte E-Mail-Adresse bei student.uts.edu.au
Titel
Zitiert von
Zitiert von
Jahr
Deep reinforcement learning for autonomous internet of things: Model, applications and challenges
L Lei, Y Tan, K Zheng, S Liu, K Zhang, X Shen
IEEE Communications Surveys & Tutorials 22 (3), 1722-1760, 2020
2222020
FedProto: Federated Prototype Learning Across Heterogeneous Clients
Y Tan, G Long, L Liu, T Zhou, Q Lu, J Jiang, C Zhang
AAAI Conference on Artificial Intelligence, AAAI-22 36 (8), 8432-8440, 2022
2152022
Federated learning for open banking
G Long, Y Tan, J Jiang, C Zhang
Federated Learning: Privacy and Incentive, 240-254, 2020
1822020
Dynamic energy dispatch based on deep reinforcement learning in IoT-driven smart isolated microgrids
L Lei, Y Tan, G Dahlenburg, W Xiang, K Zheng
IEEE internet of things journal 8 (10), 7938-7953, 2020
74*2020
Federated Learning from Pre-Trained Models: A Contrastive Learning Approach
Y Tan, G Long, J Ma, L Liu, T Zhou, J Jiang
Advances in Neural Information Processing Systems, NeurIPS-22, 2022
652022
Federated learning for privacy-preserving open innovation future on digital health
G Long, T Shen, Y Tan, L Gerrard, A Clarke, J Jiang
Humanity Driven AI: Productivity, Well-being, Sustainability and Partnership …, 2021
622021
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing
Y Tan, Y Liu, G Long, J Jiang, Q Lu, C Zhang
AAAI Conference on Artificial Intelligence, AAAI-23, 2022
382022
LSTM-based anomaly detection for non-linear dynamical system
Y Tan, C Hu, K Zhang, K Zheng, EA Davis, JS Park
IEEE access 8, 103301-103308, 2020
162020
Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning
Y Tan, C Chen, W Zhuang, X Dong, L Lyu, G Long
Thirty-seventh Conference on Neural Information Processing Systems, 2023
3*2023
An in-vehicle keyword spotting system with multi-source fusion for vehicle applications
Y Tan, K Zheng, L Lei
2019 IEEE Wireless Communications and Networking Conference (WCNC), 1-6, 2019
12019
Federated Learning from Pre-Trained Models: A Contrastive Learning Approach
Y Tan, G Long, J Ma, L Liu, T Zhou, J Jiang
ICML Workshop on Pre-training: Perspectives, Pitfalls, and Paths Forward, 2022, 0
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