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Multi-armed bandit with sub-exponential rewards

Journal Article · · Operations Research Letters

Not provided.

Research Organization:
Univ. of Michigan, Ann Arbor, MI (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
DOE Contract Number:
SC0018018
OSTI ID:
1852464
Journal Information:
Operations Research Letters, Vol. 49, Issue 5; ISSN 0167-6377
Publisher:
Elsevier
Country of Publication:
United States
Language:
English

References (9)

Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems journal January 2012
Bandits With Heavy Tail journal November 2013
Pricing of reusable resources under ambiguous distributions of demand and service time with emerging applications journal April 2020
Some aspects of the sequential design of experiments journal January 1952
Learning to Optimize via Posterior Sampling journal November 2014
Optimal Dynamic Assortment Planning with Demand Learning journal July 2013
Inventory rebalancing and vehicle routing in bike sharing systems journal March 2017
Online Learning and Online Convex Optimization journal January 2011
Introduction to Multi-Armed Bandits journal January 2019

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