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Jun 8, 2015 · We study the K-armed dueling bandit problem, a variation of the standard stochastic bandit problem where the feedback is limited to relative comparisons of a ...
The proposed algorithm is found to be the first one with a regret upper bound that matches the lower bound. Experimental comparisons of dueling bandit ...
Preference-based feedback has been well-studied in bandit settings known as dueling bandits (Yue et al., 2012;Joachims, 2009, 2011;Saha and Gopalan, 2018;Ailon ...
May 5, 2016 · We study the K-armed dueling bandit problem, a variation of the standard stochastic bandit problem where the feedback is limited to relative comparisons of a ...
Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem · Junpei KomiyamaJ. HondaH. KashimaHiroshi Nakagawa · COLT ; Copeland Dueling Bandits · M.
Sep 12, 2024 · We study the K-armed dueling bandit problem, a variation of the standard stochastic bandit problem where the feedback is limited to relative ...
Nov 5, 2024 · ... algorithm, highlighting the subtlety of this dueling bandit problem. ... lower bound for dueling bandits. For these reasons, and despite ...
Copeland dueling bandit problem: regret lower bound, optimal algorithm, and computationally efficient algorithm. Authors: Junpei Komiyama. Junpei Komiyama. The ...
2 days ago · This paper introduces a new approach for contextual dueling bandits under adversarial feedback by proposing the Robust Contextual Dueling ...
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Aug 20, 2015 · We study the $K$-armed dueling bandit problem, a variation of the standard stochastic bandit problem where the feedback is limited to ...