Bandits With Heavy Tail-Reference-Cited by-同舟云学术

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Bandits With Heavy Tail

Published:2013-11 Issue:11 Volume:59 Page:7711-7717
ISSN:0018-9448
Container-title:IEEE Transactions on Information Theory
language:
Short-container-title:IEEE Trans. Inform. Theory

Author:

Bubeck Sebastien,Cesa-Bianchi Nicolo,Lugosi Gabor

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Library and Information Sciences,Computer Science Applications,Information Systems

Link

http://xplorestaging.ieee.org/ielx7/18/6634534/06576820.pdf?arnumber=6576820

Cited by 127 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. ARFIS: An adaptive robust model for regression with heavy-tailed distribution;Information Sciences;2025-01

2. Gaussian differentially private robust mean estimation and inference;Bernoulli;2024-11-01

3. Logarithmic Regret Bounds for Continuous-Time Average-Reward Markov Decision Processes;SIAM Journal on Control and Optimization;2024-09-10

4. Non-stationary Bandits with Heavy Tail;ACM SIGMETRICS Performance Evaluation Review;2024-09-05

5. Bandits with Stochastic Experts: Constant Regret, Empirical Experts and Episodes;ACM Transactions on Modeling and Performance Evaluation of Computing Systems;2024-08-13

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