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. 2010.12866
  4. Cited By
Optimal Algorithms for Stochastic Multi-Armed Bandits with Heavy Tailed
  Rewards

Optimal Algorithms for Stochastic Multi-Armed Bandits with Heavy Tailed Rewards

24 October 2020
Kyungjae Lee
Hongjun Yang
Sungbin Lim
Songhwai Oh
ArXivPDFHTML

Papers citing "Optimal Algorithms for Stochastic Multi-Armed Bandits with Heavy Tailed Rewards"

4 / 4 papers shown
Title
uniINF: Best-of-Both-Worlds Algorithm for Parameter-Free Heavy-Tailed MABs
uniINF: Best-of-Both-Worlds Algorithm for Parameter-Free Heavy-Tailed MABs
Yu Chen
Jiatai Huang
Yan Dai
Longbo Huang
135
2
0
04 Oct 2024
Distribution oblivious, risk-aware algorithms for multi-armed bandits
  with unbounded rewards
Distribution oblivious, risk-aware algorithms for multi-armed bandits with unbounded rewards
Anmol Kagrecha
Jayakrishnan Nair
Krishna Jagannathan
50
47
0
03 Jun 2019
Sparse Markov Decision Processes with Causal Sparse Tsallis Entropy
  Regularization for Reinforcement Learning
Sparse Markov Decision Processes with Causal Sparse Tsallis Entropy Regularization for Reinforcement Learning
Kyungjae Lee
Sungjoon Choi
Songhwai Oh
49
68
0
19 Sep 2017
Bandits with heavy tail
Bandits with heavy tail
Sébastien Bubeck
Nicolò Cesa-Bianchi
Gábor Lugosi
172
290
0
08 Sep 2012
1