Results 191 to 200 of about 12,386 (222)
To Ask or Not To Ask: Human-in-the-loop Contextual Bandits with Applications in Robot-Assisted Feeding. [PDF]
IEEE Int Conf Robot AutomBanerjee R +6 more
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PianoGym: Safe post-action piano rhythm training with fatigue constraints. [PDF]
PLoS OneMeng X, Shi H, Liu N, Pan Z, Xia Y.
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Decision tree-based prediction of 5-year weight trajectories after bariatric surgery in adolescents and young adults: a retrospective cohort study from France and Sweden. [PDF]
Int J Obes (Lond)Gueorguieva I +20 more
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, 2008 We survey the literature on multi-armed bandit models and their applications in economics. The multi-armed bandit problem is a statistical decision model of an agent trying to optimize his decisions while improving his information at the same time.
Dirk Bergemann, Juuso Valimaki
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Linearly Parameterized Bandits [PDF]
Mathematics of Operations Research, 2010 We consider bandit problems involving a large (possibly infinite) collection of arms, in which the expected reward of each arm is a linear function of an r-dimensional random vector Z ∈ ℝr, where r ≥ 2. The objective is to minimize the cumulative regret and Bayes risk.
Paat Rusmevichientong +1 more
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52nd IEEE Conference on Decision and Control, 2013
Motivated by online advertising applications, we consider a version of the classical multi-armed bandit problem where there is a cost associated with pulling each arm, and a corresponding budget which limits the number of times that an arm can be pulled. We derive regret bounds on the expected reward in such a bandit problem using a modification of the
Chong Jiang, R. Srikant 0001
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Motivated by online advertising applications, we consider a version of the classical multi-armed bandit problem where there is a cost associated with pulling each arm, and a corresponding budget which limits the number of times that an arm can be pulled. We derive regret bounds on the expected reward in such a bandit problem using a modification of the
Chong Jiang, R. Srikant 0001
openaire +2 more sources
A Note on Bandits with a Twist
SIAM Journal on Discrete Mathematics, 2004A variant of the multiarmed bandit problem was recently introduced by Dimitriu, Tetali, and Winkler. For this model (and a mild generalization) we propose faster algorithms to compute the Gittins index. The indexability of such models follows from earlier work of Nash on generalized bandits.
Akshay-Kumar Katta, Jay Sethuraman
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Mostly Exploration-Free Algorithms for Contextual Bandits
Management Science, 2021Mohsen Bayati +2 more
exaly