FLAS: Computation and Communication Efficient Federated Learning via Adaptive Sampling
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Network Science and Engineering"
DOI: 10.1109/tnse.2021.3056655
Abstract: Federated learning enables collaborative deep learning over multiple clients without sharing their local data, and it becomes increasingly popular due to the good balance between data privacy and model usability. Generally, it faces the heavy… read more here.
Keywords: communication efficient; communication; federated learning; efficient federated ... See more keywords
Communication-Efficient Federated Learning Using Censored Heavy Ball Descent
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Signal and Information Processing over Networks"
DOI: 10.1109/tsipn.2022.3212315
Abstract: Distributed machine learning enables scalability and computational offloading, but requires significant levels of communication. Consequently, communication efficiency in distributed learning settings is an important consideration, especially when the communications are wireless and battery-driven devices are… read more here.
Keywords: communication efficient; heavy ball; communication; chb ... See more keywords