Abstract: Federated Learning (FL) represents a promising approach to typical privacy concerns associated with centralized Machine Learning (ML) deployments. Despite its well-known advantages, FL is ...
Abstract: Federated learning-based mobile crowdsourcing (F-MCS) leverages crowdsourcing for large-scale data perception, but it faces challenges from privacy concerns and network instability problems.
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