Abstract: Multiple response optimization (MRO) aims to obtain an optimal solution by optimizing several responses simultaneously for quality improvement. The preference parameters in the traditional ...
Asynchronous Federated Learning with non-convex client objective functions and heterogeneous dataset
Abstract: Federated Learning is a distributed machine learning paradigm that enables model training across decentralized devices holding local data, thereby preserving data privacy and reducing the ...
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