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2102.03734
Cited By
Regret Minimization in Heavy-Tailed Bandits
Annual Conference Computational Learning Theory (COLT), 2021
7 February 2021
Shubhada Agrawal
Sandeep Juneja
Wouter M. Koolen
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Papers citing
"Regret Minimization in Heavy-Tailed Bandits"
20 / 20 papers shown
Learning When Not to Learn: Risk-Sensitive Abstention in Bandits with Unbounded Rewards
Sarah Liaw
Benjamin Plaut
210
1
0
16 Oct 2025
Robust Batched Bandits
Yunwen Guo
Yunlun Shu
Gongyi Zhuo
Tianyu Wang
137
0
0
04 Oct 2025
Optimal e-value testing for properly constrained hypotheses
Eugenio Clerico
217
5
0
30 Dec 2024
Data-Driven Upper Confidence Bounds with Near-Optimal Regret for Heavy-Tailed Bandits
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Ambrus Tamás
Szabolcs Szentpéteri
Balázs Csanád Csáji
219
2
0
09 Jun 2024
Fast UCB-type algorithms for stochastic bandits with heavy and super heavy symmetric noise
Adaptive Agents and Multi-Agent Systems (AAMAS), 2024
Yuriy Dorn
Aleksandr Katrutsa
Ilgam Latypov
Andrey Pudovikov
269
3
0
10 Feb 2024
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-Adaptive Regret Minimization in Heavy-Tailed Bandits
Gianmarco Genalti
Lupo Marsigli
Nicola Gatti
Alberto Maria Metelli
308
0
0
04 Oct 2023
Nash Regret Guarantees for Linear Bandits
Neural Information Processing Systems (NeurIPS), 2023
Ayush Sawarni
Soumybrata Pal
Siddharth Barman
352
9
0
03 Oct 2023
CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic Corruption
International Conference on Algorithmic Learning Theory (ALT), 2023
Shubhada Agrawal
Timothée Mathieu
D. Basu
Odalric-Ambrym Maillard
291
4
0
28 Sep 2023
Allocating Divisible Resources on Arms with Unknown and Random Rewards
Annual Conference Computational Learning Theory (COLT), 2023
Yi Xiong
Siyuan Li
257
0
0
28 Jun 2023
Optimal Best-Arm Identification in Bandits with Access to Offline Data
Shubhada Agrawal
Sandeep Juneja
Karthikeyan Shanmugam
A. Suggala
327
7
0
15 Jun 2023
Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards
International Conference on Machine Learning (ICML), 2023
Yulian Wu
Xingyu Zhou
Sayak Ray Chowdhury
Haiyan Zhao
445
4
0
01 Jun 2023
Regret Distribution in Stochastic Bandits: Optimal Trade-off between Expectation and Tail Risk
D. Simchi-Levi
Zeyu Zheng
Feng Zhu
167
5
0
10 Apr 2023
A General Recipe for the Analysis of Randomized Multi-Armed Bandit Algorithms
Dorian Baudry
Kazuya Suzuki
Junya Honda
281
6
0
10 Mar 2023
Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits
International Conference on Machine Learning (ICML), 2023
Jongyeong Lee
Junya Honda
Chao-Kai Chiang
Masashi Sugiyama
365
4
0
03 Feb 2023
Non-Asymptotic Analysis of a UCB-based Top Two Algorithm
Neural Information Processing Systems (NeurIPS), 2022
Marc Jourdan
Rémy Degenne
501
10
0
11 Oct 2022
Multi-Armed Bandits with Self-Information Rewards
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2022
Nir Weinberger
M. Yemini
149
9
0
06 Sep 2022
Top Two Algorithms Revisited
Neural Information Processing Systems (NeurIPS), 2022
Marc Jourdan
Rémy Degenne
Dorian Baudry
R. D. Heide
E. Kaufmann
353
50
0
13 Jun 2022
Catoni-style confidence sequences for heavy-tailed mean estimation
Stochastic Processes and their Applications (SPA), 2022
Hongjian Wang
Aaditya Ramdas
937
39
0
02 Feb 2022
Regret Minimization in Isotonic, Heavy-Tailed Contextual Bandits via Adaptive Confidence Bands
S. Chatterjee
Subhabrata Sen
OffRL
214
5
0
19 Oct 2021
Optimal Best-Arm Identification Methods for Tail-Risk Measures
Shubhada Agrawal
Wouter M. Koolen
Sandeep Juneja
318
26
0
17 Aug 2020
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