Scalable Distributed Optimization of Multi-Dimensional Functions Despite Byzantine Adversaries-Reference-Cited by-同舟云学术

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Scalable Distributed Optimization of Multi-Dimensional Functions Despite Byzantine Adversaries

Published:2024 Issue: Volume:10 Page:360-375
ISSN:2373-776X
Container-title:IEEE Transactions on Signal and Information Processing over Networks
language:
Short-container-title:IEEE Trans. on Signal and Inf. Process. over Networks

Author:

Kuwaranancharoen Kananart¹^ORCID,Xin Lei²^ORCID,Sundaram Shreyas³^ORCID

Affiliation:

1. Purdue University, West Lafayette, IN, USA

2. Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong

3. Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA

Funder

National Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

https://ieeexplore.ieee.org/ielam/6884276/10380708/10478151-aam.pdf

Reference52 articles.

1. Distributed asynchronous deterministic and stochastic gradient optimization algorithms

2. Optimal Scaling of a Gradient Method for Distributed Resource Allocation

3. A control perspective for centralized and distributed convex optimization

4. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers

5. Decentralized Quasi-Newton Methods

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