Multi-Environment Meta-Learning in Stochastic Linear Bandits-Reference-Cited by-同舟云学术

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Multi-Environment Meta-Learning in Stochastic Linear Bandits

Published:2022-06-26 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Symposium on Information Theory (ISIT)
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Author:

Moradipari Ahmadreza¹,Ghavamzadeh Mohammad²,Rajabzadeh Taha³,Thrampoulidis Christos⁴,Alizadeh Mahnoosh¹

Affiliation:

1. University of California,Santa Barbara

2. Google Research

3. Stanford University

4. University of British Columbia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9834325/9834269/09834636.pdf?arnumber=9834636

Reference41 articles.

1. Thompson sampling with a mixture prior;hong,2021

2. Meta-thompson sampling;kveton,2021

3. Multi-task linear bandits;soare;NIPS workshop on Transfer and Multi-Task Learning Theory meets Practice,2014

4. Multi-task learning for contextual bandits;deshmukh,2017

5. Transfer Learning in Multi-Armed Bandits: A Causal Approach

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