2013
NIPS
NeurIPS 2013
From Bandits to Experts: A Tale of Domination and Independence
Abstract
We consider the partial observability model for multi-armed bandits, introduced by Mannor and Shamir (2011). Our main result is a characterization of regret in the directed observability model in terms of the dominating and independence numbers of the observability graph. We also show that in the undirected case, the learner can achieve optimal regret without even accessing the observability graph before selecting an action. Both results are shown using variants of the Exp3 algorithm operating on the observability graph in a time-efficient manner.
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Interdisciplinary Bridge
— Machine Learning and Mathematics & Optimization
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Keyword Pioneer
— regret
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Hot Topic Early Bird
— multi-armed bandit
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning
Authors
Topics
Machine Learning > Optimization & Theory > Theory
Mathematics & Optimization > Mathematics > Graph Theory
Mathematics & Optimization > Optimization > Online Algorithms
Machine Learning > Learning Types > Online Learning
Machine Learning > Optimization & Theory > Online Algorithms
Machine Learning > Learning Types > Multi-Armed Bandits
Machine Learning > Core Methods > Optimization