Optimal Device Selection in Federated Learning for Resource-Constrained Edge Networks-Reference-Cited by-同舟云学术

Optimal Device Selection in Federated Learning for Resource-Constrained Edge Networks

Author:

Kushwaha Deepali¹^ORCID,Redhu Surender²^ORCID,Brinton Christopher G.³^ORCID,Hegde Rajesh M.¹^ORCID

Affiliation:

1. Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, India

2. Department of Information and Communication Technology, University of Agder, Grimstad, Norway

3. Department of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA

Funder

Office of Naval Research

National Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

Reference45 articles.

1. Federated collaborative filtering for privacy-preserving personalized recommendation system;ammad-ud-din;arXiv 1901 09888,2019

2. Federated learning with quantized global model updates;amiri;arXiv 2006 10672,2020

4. DoubleSqueeze: Parallel stochastic gradient descent with double-pass error-compensated compression;tang;Proc Int Conf Mach Learn,2019

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