ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2106.04207
  4. Cited By
Cooperative Stochastic Multi-agent Multi-armed Bandits Robust to
  Adversarial Corruptions

Cooperative Stochastic Multi-agent Multi-armed Bandits Robust to Adversarial Corruptions

8 June 2021
Junyan Liu
Shuai Li
Dapeng Li
ArXiv (abs)PDFHTML

Papers citing "Cooperative Stochastic Multi-agent Multi-armed Bandits Robust to Adversarial Corruptions"

24 / 24 papers shown
Title
Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic
  and Adversarial Linear Bandits Simultaneously
Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously
Chung-Wei Lee
Haipeng Luo
Chen-Yu Wei
Mengxiao Zhang
Xiaojin Zhang
81
49
0
11 Feb 2021
Cooperative Multi-Agent Bandits with Heavy Tails
Cooperative Multi-Agent Bandits with Heavy Tails
Abhimanyu Dubey
Alex Pentland
41
50
0
14 Aug 2020
Corruption-Tolerant Gaussian Process Bandit Optimization
Corruption-Tolerant Gaussian Process Bandit Optimization
Ilija Bogunovic
Andreas Krause
Jonathan Scarlett
86
52
0
04 Mar 2020
Distributed Cooperative Decision Making in Multi-agent Multi-armed
  Bandits
Distributed Cooperative Decision Making in Multi-agent Multi-armed Bandits
Peter Landgren
Vaibhav Srivastava
Naomi Ehrich Leonard
132
68
0
03 Mar 2020
Decentralized Multi-player Multi-armed Bandits with No Collision
  Information
Decentralized Multi-player Multi-armed Bandits with No Collision Information
Chengshuai Shi
Wei Xiong
Cong Shen
Jing Yang
68
36
0
29 Feb 2020
My Fair Bandit: Distributed Learning of Max-Min Fairness with
  Multi-player Bandits
My Fair Bandit: Distributed Learning of Max-Min Fairness with Multi-player Bandits
Ilai Bistritz
Tavor Z. Baharav
Amir Leshem
Nicholas Bambos
FaML
63
37
0
23 Feb 2020
Social Learning in Multi Agent Multi Armed Bandits
Social Learning in Multi Agent Multi Armed Bandits
Abishek Sankararaman
A. Ganesh
Sanjay Shakkottai
75
86
0
04 Oct 2019
Stochastic Linear Optimization with Adversarial Corruption
Stochastic Linear Optimization with Adversarial Corruption
Yingkai Li
Edmund Y. Lou
Liren Shan
AAML
52
42
0
04 Sep 2019
Individual Regret in Cooperative Nonstochastic Multi-Armed Bandits
Individual Regret in Cooperative Nonstochastic Multi-Armed Bandits
Yogev Bar-On
Yishay Mansour
48
42
0
07 Jul 2019
Collaborative Learning with Limited Interaction: Tight Bounds for
  Distributed Exploration in Multi-Armed Bandits
Collaborative Learning with Limited Interaction: Tight Bounds for Distributed Exploration in Multi-Armed Bandits
Chao Tao
Qin Zhang
Yuanshuo Zhou
FedML
39
61
0
05 Apr 2019
Better Algorithms for Stochastic Bandits with Adversarial Corruptions
Better Algorithms for Stochastic Bandits with Adversarial Corruptions
Anupam Gupta
Tomer Koren
Kunal Talwar
AAML
117
152
0
22 Feb 2019
Multi-Player Bandits: The Adversarial Case
Multi-Player Bandits: The Adversarial Case
Pragnya Alatur
Kfir Y. Levy
Andreas Krause
AAML
51
37
0
21 Feb 2019
Cooperative Online Learning: Keeping your Neighbors Updated
Cooperative Online Learning: Keeping your Neighbors Updated
Nicolò Cesa-Bianchi
Tommaso Cesari
C. Monteleoni
42
35
0
23 Jan 2019
Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits
Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits
Julian Zimmert
Yevgeny Seldin
AAML
169
181
0
19 Jul 2018
Stochastic bandits robust to adversarial corruptions
Stochastic bandits robust to adversarial corruptions
Thodoris Lykouris
Vahab Mirrokni
R. Leme
AAML
149
204
0
25 Mar 2018
Distributed Cooperative Decision-Making in Multiarmed Bandits:
  Frequentist and Bayesian Algorithms
Distributed Cooperative Decision-Making in Multiarmed Bandits: Frequentist and Bayesian Algorithms
Peter Landgren
Vaibhav Srivastava
Naomi Ehrich Leonard
52
111
0
02 Jun 2016
An algorithm with nearly optimal pseudo-regret for both stochastic and
  adversarial bandits
An algorithm with nearly optimal pseudo-regret for both stochastic and adversarial bandits
P. Auer
Chao-Kai Chiang
72
111
0
27 May 2016
Delay and Cooperation in Nonstochastic Bandits
Delay and Cooperation in Nonstochastic Bandits
Nicolò Cesa-Bianchi
Claudio Gentile
Yishay Mansour
Alberto Minora
49
145
0
15 Feb 2016
On Distributed Cooperative Decision-Making in Multiarmed Bandits
On Distributed Cooperative Decision-Making in Multiarmed Bandits
Peter Landgren
Vaibhav Srivastava
Naomi Ehrich Leonard
63
78
0
21 Dec 2015
Distributed Exploration in Multi-Armed Bandits
Distributed Exploration in Multi-Armed Bandits
Eshcar Hillel
Zohar Karnin
Tomer Koren
R. Lempel
O. Somekh
151
107
0
04 Nov 2013
Distributed Non-Stochastic Experts
Distributed Non-Stochastic Experts
Varun Kanade
Zhenming Liu
B. Radunovic
OffRL
69
23
0
14 Nov 2012
Multiple Identifications in Multi-Armed Bandits
Multiple Identifications in Multi-Armed Bandits
Sébastien Bubeck
Tengyao Wang
N. Viswanathan
114
174
0
14 May 2012
Learning in A Changing World: Restless Multi-Armed Bandit with Unknown
  Dynamics
Learning in A Changing World: Restless Multi-Armed Bandit with Unknown Dynamics
Haoyang Liu
Keqin Liu
Qing Zhao
120
159
0
22 Nov 2010
Contextual Bandit Algorithms with Supervised Learning Guarantees
Contextual Bandit Algorithms with Supervised Learning Guarantees
A. Beygelzimer
John Langford
Lihong Li
L. Reyzin
Robert Schapire
OffRL
199
325
0
22 Feb 2010
1