PAC-Bayes Bounds for Bandit Problems: A Survey and Experimental Comparison-Reference-Cited by-同舟云学术

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PAC-Bayes Bounds for Bandit Problems: A Survey and Experimental Comparison

Published:2023-12 Issue:12 Volume:45 Page:15308-15327
ISSN:0162-8828
Container-title:IEEE Transactions on Pattern Analysis and Machine Intelligence
language:
Short-container-title:IEEE Trans. Pattern Anal. Mach. Intell.

Author:

Flynn Hamish¹^ORCID,Reeb David¹^ORCID,Kandemir Melih²^ORCID,Peters Jan³^ORCID

Affiliation:

1. Bosch Center for Artificial Intelligence, Renningen, Germany

2. Department of Mathematics and Computer Science (IMADA), University of Southern Denmark, Odense, Denmark

3. Intelligent Autonomous Systems Group, Technische Universität Darmstadt, Darmstadt, Germany

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software

Link

http://xplorestaging.ieee.org/ielx7/34/10308548/10224540.pdf?arnumber=10224540

Reference116 articles.

1. A tutorial on PAC-Bayesian theory;laviolette;Proc Talk NIPS Workshop (Almost) 50 Shades PAC-Bayesian Learn PAC-Bayesian Trends Insights,2017

2. Bandit Algorithms

3. Distribution-Dependent PAC-Bayes Priors

4. Dichotomize and generalize: PAC-Bayesian binary activated deep neural networks;letarte;Proc Int Conf Neural Inf Process,2019

5. (Not) bounding the true error;langford;Proc Int Conf Neural Inf Process,2002

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