This robust growth is being propelled by a confluence of critical factors, including a rising global prevalence of thyroid ...
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 ...
Measuring ROI can be tricky, so we spoke with several CIOs about how to make sure your board or leadership sees it.
Abstract: Constrained many-objective optimization problems (CMaOPs) include the optimization of many objective functions and satisfaction of constraints, which seriously enhance the difficulty of ...
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