Migrating federated learning to centralized learning with the leverage of unlabeled data

Author:

Wang Xiaoya,Zhu Tianqing,Ren Wei,Zhang Dongmei,Xiong Ping

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Hardware and Architecture,Human-Computer Interaction,Information Systems,Software

Reference40 articles.

1. McMahan B, Moore E, Ramage D, Hampson S, y Arcas BA (2017) Communication-efficient learning of deep networks from decentralized data. In: Artificial intelligence and statistics, pp. 1273–1282

2. Lim WYB, Luong NC, Hoang DT, Jiao Y, Liang Y-C, Yang Q, Niyato D, Miao C (2020) Federated learning in mobile edge networks: a comprehensive survey. IEEE Commun Surv Tutor 22:2031–2063

3. Zhao Y, Li M, Lai L, Suda N, Civin D, Chandra V (2018) Federated learning with non-iid data. arXiv preprint arXiv:1806.00582

4. Li X, Huang K, Yang W, Wang S, Zhang Z (2020) On the convergence of fedavg on non-iid data. In: International conference on learning representations

5. Jeong W, Yoon J, Yang E, Hwang SJ (2021) Federated semi-supervised learning with inter-client consistency and disjoint learning. In: International conference on learning representations

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