
The Countablearmed Bandit with Vanishing Arms
We consider a bandit problem with countably many arms, partitioned into ...
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A Closer Look at the Worstcase Behavior of Multiarmed Bandit Algorithms
One of the key drivers of complexity in the classical (stochastic) multi...
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From Finite to CountableArmed Bandits
We consider a stochastic bandit problem with countably many arms that be...
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Dynamic Pricing and Learning under the Bass Model
We consider a novel formulation of the dynamic pricing and demand learni...
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Learning to Stop with Surprisingly Few Samples
We consider a discounted infinite horizon optimal stopping problem. If t...
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Towards Optimal Problem Dependent Generalization Error Bounds in Statistical Learning Theory
We study problemdependent rates, i.e., generalization errors that scale...
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SparsityAgnostic Lasso Bandit
We consider a stochastic contextual bandit problem where the dimension d...
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Upper Counterfactual Confidence Bounds: a New Optimism Principle for Contextual Bandits
The principle of optimism in the face of uncertainty is one of the most ...
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Discriminative Learning via Adaptive Questioning
We consider the problem of designing an adaptive sequence of questions t...
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A Unified Approach for Solving Sequential Selection Problems
In this paper we develop a unified approach for solving a wide class of ...
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A General Approach to MultiArmed Bandits Under Risk Criteria
Different riskrelated criteria have received recent interest in learnin...
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Optimal ExplorationExploitation in a MultiArmedBandit Problem with Nonstationary Rewards
In a multiarmed bandit (MAB) problem a gambler needs to choose at each ...
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Assaf Zeevi
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