Implementation of Federated Learning Algorithms for Non Independent and Identically Distributed Data
Abstract: Federated Learning (FL) has emerged as a transformative approach for training machine learning models across decentralized data sources while preserving privacy. This study evaluates the ...
Abstract: This paper investigates the fixed-time distributed optimization problem of first-order multi-agent systems with strongly convex local cost functions and consensus constraints. To address ...
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