Semi-Decentralized Federated Learning with Collaborative Relaying

Author:

Yemini Michal1,Saha Rajarshi2,Ozfatura Emre3,Gunduz Deniz3,Goldsmith Andrea J.1

Affiliation:

1. Princeton University

2. Stanford University

3. Imperial College London

Publisher

IEEE

Reference50 articles.

1. Achieving linear speedup with partial worker participation in non-IID federated learning;yang;International Conference on Learning Representations,2021

2. Hybrid local SGD for federated learning with heterogeneous communications,0

3. Stochastic gradient push for distributed deep learning;assran;36th Int Conf Mach Learning,2019

4. MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling

5. A unified theory of decentralized SGD with changing topology and local updates;koloskova;37th Int Conf Mach Learn,2020

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