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Adaptive Best-of-Both-Worlds Algorithm for Heavy-Tailed Multi-Armed
  Bandits
v1v2 (latest)

Adaptive Best-of-Both-Worlds Algorithm for Heavy-Tailed Multi-Armed Bandits

International Conference on Machine Learning (ICML), 2022
28 January 2022
Jiatai Huang
Yan Dai
Longbo Huang
ArXiv (abs)PDFHTML

Papers citing "Adaptive Best-of-Both-Worlds Algorithm for Heavy-Tailed Multi-Armed Bandits"

13 / 13 papers shown
When Lower-Order Terms Dominate: Adaptive Expert Algorithms for Heavy-Tailed Losses
When Lower-Order Terms Dominate: Adaptive Expert Algorithms for Heavy-Tailed Losses
Antoine Moulin
Emmanuel Esposito
Dirk van der Hoeven
276
0
0
02 Jun 2025
Faster Rates for Private Adversarial Bandits
Faster Rates for Private Adversarial Bandits
Hilal Asi
Vinod Raman
Kunal Talwar
PICVFedML
296
0
0
27 May 2025
Heavy-Tailed Linear Bandits: Huber Regression with One-Pass Update
Heavy-Tailed Linear Bandits: Huber Regression with One-Pass Update
Jing Wang
Yu Zhang
Peng Zhao
Zhi Zhou
388
3
0
01 Mar 2025
Catoni Contextual Bandits are Robust to Heavy-tailed Rewards
Catoni Contextual Bandits are Robust to Heavy-tailed Rewards
Chenlu Ye
Yujia Jin
Alekh Agarwal
Tong Zhang
467
1
0
04 Feb 2025
uniINF: Best-of-Both-Worlds Algorithm for Parameter-Free Heavy-Tailed MABs
uniINF: Best-of-Both-Worlds Algorithm for Parameter-Free Heavy-Tailed MABsInternational Conference on Learning Representations (ICLR), 2024
Yu Chen
Jiatai Huang
Yan Dai
Longbo Huang
430
6
0
04 Oct 2024
Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive
  Analysis and Best-of-Both-Worlds
Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds
Shinji Ito
Taira Tsuchiya
Junya Honda
454
9
0
01 Mar 2024
Fast UCB-type algorithms for stochastic bandits with heavy and super
  heavy symmetric noise
Fast UCB-type algorithms for stochastic bandits with heavy and super heavy symmetric noiseAdaptive Agents and Multi-Agent Systems (AAMAS), 2024
Yuriy Dorn
Aleksandr Katrutsa
Ilgam Latypov
Andrey Pudovikov
226
3
0
10 Feb 2024
Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed
  Rewards
Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed RewardsNeural Information Processing Systems (NeurIPS), 2023
Bo Xue
Yimu Wang
Yuanyu Wan
Jinfeng Yi
Lijun Zhang
239
9
0
28 Oct 2023
Towards Robust Offline Reinforcement Learning under Diverse Data
  Corruption
Towards Robust Offline Reinforcement Learning under Diverse Data Corruption
Rui Yang
Han Zhong
Jiawei Xu
Amy Zhang
Chong Zhang
Lei Han
Tong Zhang
OffRLOnRL
454
26
0
19 Oct 2023
$(ε, u)$-Adaptive Regret Minimization in Heavy-Tailed Bandits
(ε,u)(ε, u)(ε,u)-Adaptive Regret Minimization in Heavy-Tailed Bandits
Gianmarco Genalti
Lupo Marsigli
Nicola Gatti
Alberto Maria Metelli
264
0
0
04 Oct 2023
Implicitly normalized forecaster with clipping for linear and non-linear
  heavy-tailed multi-armed bandits
Implicitly normalized forecaster with clipping for linear and non-linear heavy-tailed multi-armed banditsComputational Management Science (CMS), 2023
Yuriy Dorn
Kornilov Nikita
N. Kutuzov
A. Nazin
Eduard A. Gorbunov
Alexander Gasnikov
329
5
0
11 May 2023
A Blackbox Approach to Best of Both Worlds in Bandits and Beyond
A Blackbox Approach to Best of Both Worlds in Bandits and BeyondAnnual Conference Computational Learning Theory (COLT), 2023
Christoph Dann
Chen-Yu Wei
Julian Zimmert
249
29
0
20 Feb 2023
Best-of-Both-Worlds Algorithms for Partial Monitoring
Best-of-Both-Worlds Algorithms for Partial MonitoringInternational Conference on Algorithmic Learning Theory (ALT), 2022
Taira Tsuchiya
Shinji Ito
Junya Honda
462
18
0
29 Jul 2022
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