Model Pruning for Distributed Learning Over the Air
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2024.3486169
Abstract: Analog over-the-air (A-OTA) computing is an effective approach to achieving distributed learning among multiple end-user devices within a bandwidth-constrained spectrum. In this paradigm, users’ intermediate parameters, such as gradients, are modulated onto a set of… read more here.
Keywords: pruning distributed; distributed learning; model pruning; learning air ... See more keywords
Personalized Federated Learning Over the Air
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Wireless Communications"
DOI: 10.1109/twc.2025.3573777
Abstract: We propose an effective approach toward implementing personalized federated learning at the edge of wireless networks. The scheme employs a bi-level optimization framework to personalize the federated learning models, and leverages over-the-air computations for model… read more here.
Keywords: air computations; learning models; learning air; federated learning ... See more keywords