Federated multi-armed bandits(FMAB)是新的bandit范式,主要灵感来源于cognitive radio 和recommender systems的实际应用场景。这篇论文提出了一个通用型FMAB框架,并研究了该框架下的两种模型。 首先研究了近似模型,在该近似模型中,不同的local model都是global model 的服从于一个未知分布的随机实现。在这个近似模型中,...
SAMBA: A Generic Framework for Secure Federated Multi-Armed Bandits (Extended Abstract) [pdf] [code] Fedstellar: A Platform for Training Models in a Privacy-preserving and Decentralized Fashion [pdf] A Survey of Federated Evaluation in Federated Learning [pdf] Denial-of-Service or Fine-Grained ...
Federated Multi-Armed Bandits University of Virginia codevideo On the Convergence of Communication-Efficient Local SGD for Federated Learning Temple University;University of Pittsburgh video FLAME: Differentially Private Federated Learning in the Shuffle Model Renmin University of China;Kyoto University videoco...
First, a stratified sampling method is proposed to coordinate the selection of clients in the same round to mitigate system heterogeneity, and multi-armed bandits (MAB) are used to eliminate the bias caused by stratified sampling. Secondly, a novel client selection scheme is proposed to explore ...
Federated Multi-Armed Bandits University of Virginia codevideo On the Convergence of Communication-Efficient Local SGD for Federated Learning Temple University;University of Pittsburgh video FLAME: Differentially Private Federated Learning in the Shuffle Model Renmin University of China;Kyoto University videoco...
Federated Multi-Armed Bandits University of Virginia codevideo On the Convergence of Communication-Efficient Local SGD for Federated Learning Temple University;University of Pittsburgh video FLAME: Differentially Private Federated Learning in the Shuffle Model Renmin University of China;Kyoto University videoco...
Federated Multi-Armed Bandits University of Virginia codevideo On the Convergence of Communication-Efficient Local SGD for Federated Learning Temple University;University of Pittsburgh video FLAME: Differentially Private Federated Learning in the Shuffle Model Renmin University of China;Kyoto University videoco...
Federated Multi-Armed Bandits AAAI 2021(University of Virginia) codevideo FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization AISTATS 2020(UC Santa Barbara; UT Austin) videoSupplementary 16. Graph Neural Networks This section is partially refers to this rep...
Federated Multi-Armed Bandits University of Virginia codevideo On the Convergence of Communication-Efficient Local SGD for Federated Learning Temple University;University of Pittsburgh video FLAME: Differentially Private Federated Learning in the Shuffle Model Renmin University of China;Kyoto University videoco...
Federated Multi-Armed Bandits University of Virginia codevideo On the Convergence of Communication-Efficient Local SGD for Federated Learning Temple University;University of Pittsburgh video FLAME: Differentially Private Federated Learning in the Shuffle Model Renmin University of China;Kyoto University videoco...