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Dueling Bandits With Weak Regret
We consider online content recommendation with implicit feedback through pairwise comparisons, formalized as the so-called dueling bandit problem.
The Bayesian Linear Information Filtering Problem
We present a Bayesian sequential decision-making formulation of the information filtering problem, in which an algorithm presents items (news articles, scientific papers, tweets) arriving in a stream, and learns relevance from user feedback on presented items.
Dueling Bandits with Dependent Arms
We study dueling bandits with weak utility-based regret when preferences over arms have a total order and carry observable feature vectors.
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