FedHybrid: A Hybrid Federated Optimization Method for Heterogeneous Clients-Reference-Cited by-同舟云学术

FedHybrid: A Hybrid Federated Optimization Method for Heterogeneous Clients

Published:2023 Issue: Volume:71 Page:150-163
ISSN:1053-587X
Container-title:IEEE Transactions on Signal Processing
language:
Short-container-title:IEEE Trans. Signal Process.

Author:

Niu Xiaochun¹^ORCID,Wei Ermin²^ORCID

Affiliation:

1. Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL, USA

2. Department of Electrical and Computer Engineering, Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL, USA

Funder

National Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Signal Processing

Link

https://ieeexplore.ieee.org/ielam/78/10040758/10026496-aam.pdf

Reference52 articles.

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3. GIANT: Globally improved approximate newton method for distributed optimization;wang;Proc Adv Neural Inf Process Syst,0

4. Disco: Distributed optimization for self-concordant empirical loss;zhang;Proc Int Conf Mach Learn,0

5. Federated learning based on dynamic regularization;acar;Proc Int Conf Learn Representations,0

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