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Harnessing the Power of Federated Learning in Federated Contextual
  Bandits

Harnessing the Power of Federated Learning in Federated Contextual Bandits

26 December 2023
Chengshuai Shi
Ruida Zhou
Kun Yang
Cong Shen
    FedML
ArXivPDFHTML

Papers citing "Harnessing the Power of Federated Learning in Federated Contextual Bandits"

7 / 7 papers shown
Title
Near-Optimal Collaborative Learning in Bandits
Near-Optimal Collaborative Learning in Bandits
Clémence Réda
Sattar Vakili
E. Kaufmann
FedML
17
20
0
31 May 2022
Distributed Contextual Linear Bandits with Minimax Optimal Communication
  Cost
Distributed Contextual Linear Bandits with Minimax Optimal Communication Cost
Sanae Amani
Tor Lattimore
András Gyorgy
Lin F. Yang
FedML
25
9
0
26 May 2022
Byzantine-Robust Federated Learning with Optimal Statistical Rates and
  Privacy Guarantees
Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees
Banghua Zhu
Lun Wang
Qi Pang
Shuai Wang
Jiantao Jiao
D. Song
Michael I. Jordan
FedML
91
30
0
24 May 2022
Communication Efficient Federated Learning for Generalized Linear
  Bandits
Communication Efficient Federated Learning for Generalized Linear Bandits
Chuanhao Li
Hongning Wang
FedML
6
13
0
02 Feb 2022
Asynchronous Upper Confidence Bound Algorithms for Federated Linear
  Bandits
Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits
Chuanhao Li
Hongning Wang
FedML
11
35
0
04 Oct 2021
Federated Multi-Armed Bandits
Federated Multi-Armed Bandits
Chengshuai Shi
Cong Shen
FedML
47
91
0
28 Jan 2021
Federated Bandit: A Gossiping Approach
Federated Bandit: A Gossiping Approach
Zhaowei Zhu
Jingxuan Zhu
Ji Liu
Yang Liu
FedML
129
83
0
24 Oct 2020
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