Applications of Multi-Armed Bandits part2(Machine Learning)
Client Selection for Generalization in Accelerated Federated Learning: A Multi-Armed Bandit Approach(arXiv) Author : Dan Ben Ami, Kobi Cohen, Qing Zhao Abstract : Federated learning (FL) is an emerging machine learning (ML) paradigm used to train models across multiple nodes (i.e., clients) holding local data sets, without explicitly exchanging the…
Applications of Multi-Armed Bandits part2(Machine Learning) Client Selection for Generalization in Accelerated Federated Learning: A Multi-Armed Bandit Approach(arXiv) Author : Dan Ben Ami, Kobi Cohen, Qing Zhao Abstract : Federated learning (FL) is an emerging machine learning (ML) paradigm used to train models across multiple nodes (i.e., clients) holding local data sets, without explicitly exchanging the… machine-learning
Applications MultiArmed Bandits part2Machine Learning Client Selection Generalization Accelerated Federated Learning MultiArmed Bandit ApproacharXiv Author Dan Ben Ami Kobi Cohen Qing Zhao Abstract Federated learning FL emerging machine learning ML paradigm used train model across multiple node ie client holding local data set without explicitly exchanging the… machinelearning