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Imprese e certificazione di genere: il bilancio è magro | B. Martini
La prassi Uni 125/2022 che definisce le linee guida sul sistema di gestione per la parità di genere nelle imprese è stata approvata quattro anni fa. I risultati ottenuti fin qui sono legati agli incentivi, non a un vero cambiamento culturale.
Federated Learning in Dynamic and Heterogeneous Environments: Advantages, Performances, and Privacy Problems
1. Introduction Federated Learning (FL) is a new approach to machine learning that allows you to train models on data distributed across different locations without the need to centralize them. In this way, the information contained in large quantities of data can be exploited without compromising the privacy and security of the data themselves.
Federated Learning in Dynamic and Heterogeneous Environments: Advantages, Performances, and Privacy Problems
Preprint Article Version 1 This version is not peer-reviewed Version 1 : Received: 28 August 2024 / Approved: 29 August 2024 / Online: 29 August 2024 (09:18:48 CEST) Liberti, F.; Berardi, D.; Martini, B. Federated Learning in Dynamic and Heterogeneous Environments: Advantages, Performances, and Privacy Problems. Preprints 2024, 2024082125. https://doi.org/10.20944/preprints202408.2125.v1 Liberti, F.; Berardi, D.; Martini, B.
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