Multichannel ALOHA Optimization for Federated Learning With Multiple Models-Reference-Cited by-同舟云学术

Multichannel ALOHA Optimization for Federated Learning With Multiple Models

Author:

da Silva Rafael Valente¹^ORCID,Choi Jinho²^ORCID,Park Jihong²^ORCID,Brante Glauber³^ORCID,Souza Richard Demo¹^ORCID

Affiliation:

1. Department of Electrical and Electronics Engineering, Federal University of Santa Catarina, Florianópolis, Brazil

2. School of Information Technology, Deakin University, Burwood, VIC, Australia

3. CPGEI, Federal University of Technology-Paraná, Curitiba, Brazil

Funder

CNPq, Brazil

RNP/MCTIC, Brazil

Australian Government through the Australian Research Council’s Discovery Projects Funding Scheme

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Link

Reference17 articles.

1. Communication-efficient distributed learning via lazily aggregated quantized gradients;sun;Proc Adv Neural Inf Process Syst,2019

4. The ALOHA system: Another alternative for computer communications;abramson;Proc ACM AFIPS,1970

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