Securely Aggregated Coded Matrix Inversion

Author:

Charalambides Neophytos1ORCID,Pilanci Mert2ORCID,Hero Alfred O.1ORCID

Affiliation:

1. Electrical Engineering and Computer Science Department, University of Michigan, Ann Arbor, MI, USA

2. Electrical Engineering Department, Stanford University, Stanford, CA, USA

Funder

U.S. Army Research Office

ARO Early Career Award

U.S. Department of Energy

U.S. National Science Foundation

NSF CAREER Award

Stanford Precourt Institute

ACCESS–AI Chip Center for Emerging Smart Systems through InnoHK, Hong Kong, SAR

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Medicine

Reference53 articles.

1. CodedPaddedFL and CodedSecAgg: Straggler mitigation and secure aggregation in federated learning;schlegel;arXiv 2112 08909,2021

2. Coded Computing for Low-Latency Federated Learning Over Wireless Edge Networks

3. Computational Code-Based Privacy in Coded Federated Learning

4. Coding for straggler mitigation in federated learning;kumar;arXiv 2109 15226,2021

5. Sequential Lagrange multiplier condition forϵ-optimal solution in convex programming

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1. Coded Federated Learning for Communication-Efficient Edge Computing: A Survey;IEEE Open Journal of the Communications Society;2024

2. Iterative Sketching for Secure Coded Regression;IEEE Journal on Selected Areas in Information Theory;2024

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