Behave Differently when Clustering: A Semi-asynchronous Federated Learning Approach for IoT
Author:
Affiliation:
1. University of Helsinki, Helsinki, Finland
2. Norwegian University of Science and Technolog, Gjøvik, Norway
3. The Hong Kong University of Science and Technology, Helsinki, Hong Kong and University of Helsinki, Kowloon, Finland
Abstract
Funder
Guangzhou Municipal Nansha District Science and Technology Bureau
Nordic University Cooperation on Edge Intelligence
Publisher
Association for Computing Machinery (ACM)
Link
https://dl.acm.org/doi/pdf/10.1145/3639825
Reference55 articles.
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3. Pervasive AI for IoT Applications: A Survey on Resource-Efficient Distributed Artificial Intelligence
4. Daniel J. Beutel Taner Topal Akhil Mathur Xinchi Qiu Javier Fernandez-Marques Yan Gao Lorenzo Sani Kwing Hei Li Titouan Parcollet Pedro Porto Buarque de Gusmão and Nicholas D. Lane. 2020. Flower: A Friendly Federated Learning Research Framework. Retrieved from https://arxiv.org/abs/2007.14390. 10.48550/ARXIV.2007.14390
5. Sebastian Caldas Sai Meher Karthik Duddu Peter Wu Tian Li Jakub Konečnỳ H. Brendan McMahan Virginia Smith and Ameet Talwalkar. 2018. Leaf: A benchmark for federated settings. Retrieved from https://arXiv:1812.01097
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