Abstract: Split learning (SL) aims to protect user data privacy by distributing deep models between the client-server and keeping private data locally. In SL training with multiple clients, the local ...
Professionals worldwide gain standardized recognition for web development skills through assessment-based certification ...
Abstract: Federated Learning is a paradigm at the intersection of Machine Learning and Distributed Computing. The fundamental idea is that multiple agents collaborate to train a common model without ...
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