FedMint: Intelligent Bilateral Client Selection in Federated Learning with Newcomer IoT Devices. (arXiv:2211.01805v1 [cs.LG])

Federated Learning (FL) is a novel distributed privacy-preserving learning
paradigm, which enables the collaboration among several participants (e.g.,
Internet of Things devices) for the training of machine learning models.
However, selecting the participants that would contribute to this collaborative
training is highly challenging. Adopting a random selection strategy would
entail substantial problems due to the heterogeneity in terms of data quality,
and computational and communication resources across the participants. Although
several approaches have been proposed in the literature to overcome …

client devices federated learning iot iot devices