Federated Learning Tutorial

Federated Learning for All: A Reinforcement Learning-Based Approach for Ensuring Fairness in Client Selection

Abstract: In federated learning, selecting participating devices (clients) is critical due to their inherent diversity. Clients typically hold non-IID data and possess varying computational and ...

IEEE

A Verifiable Federated Learning Scheme With Privacy-Preserving in MCS

Abstract: The popularity of edge smart devices and the explosive growth of generated data have driven the development of mobile crowd sensing (MCS). Also, federated learning (FL), as a new paradigm of ...

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Federated Learning for All: A Reinforcement Learning-Based Approach for Ensuring Fairness in Client Selection

A Verifiable Federated Learning Scheme With Privacy-Preserving in MCS

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