Results 181 to 190 of about 497,803 (209)

Cross-frequency coordination in a hippocampo-cortical circuit during probabilistic reversal learning. [PDF]

Commun Biol
Aguilera A, Espinosa N, Caneo M, Lazcano G, Lara-Vasquez A, Fuentealba P.   +5 more
europepmc   +1 more source

Investigating Learning, Decision-Making, and Mental Health in Pregnancy: Insights From a UK Cohort Study. [PDF]

Comput Psychiatr
Costantini I, Montout A, Moran P, Kounali D, Pearson RM, Ludwig CJH.   +5 more
europepmc   +1 more source

Contextual Bandits With Cross-Learning

Mathematics of Operations Research, 2023
In the classic contextual bandits problem, in each round t, a learner observes some context c, chooses some action i to perform, and receives some reward [Formula: see text]. We consider the variant of this problem in which in addition to receiving the reward [Formula: see text], the learner also learns the values of [Formula: see text] for some other
Mohammad Mahdian, Santiago R. Balseiro, Negin Golrezaei   +2 more
exaly   +7 more sources

Adaptive Metamorphic Testing With Contextual Bandits [PDF]

Journal of Systems and Software, 2020
Metamorphic Testing is a software testing paradigm which aims at using necessary properties of a system-under-test, called metamorphic relations, to either check its expected outputs, or to generate new test cases. Metamorphic Testing has been successful to test programs for which a full oracle is not available or to test programs for which there are ...
Arnaud Gotlieb, Helge Spieker
exaly   +4 more sources

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Contextual Bandits in a Collaborative Environment

Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 2016
Contextual bandit algorithms provide principled online learning solutions to find optimal trade-offs between exploration and exploitation with companion side-information. They have been extensively used in many important practical scenarios, such as display advertising and content recommendation.
Qingyun Wu, Huazheng Wang, Quanquan Gu, Hongning Wang   +3 more
openaire   +2 more sources

Mixed-Effects Contextual Bandits

Proceedings of the AAAI Conference on Artificial Intelligence
We study a novel variant of a contextual bandit problem with multi-dimensional reward feedback formulated as a mixed-effects model, where the correlations between multiple feedback are induced by sharing stochastic coefficients called random effects.
Kyungbok Lee, Myunghee Cho Paik, Min-hwan Oh, Gi-Soo Kim   +3 more
openaire   +1 more source

Mostly Exploration-Free Algorithms for Contextual Bandits

Management Science, 2021
Mohsen Bayati, Hamsa Bastani, Khashayar Khosravi   +2 more
exaly  

Diversity in News Recommendations Using Contextual Bandits

Expert Systems With Applications, 2022
Guanglin Xu, Maciej Rysz, Alexander Semenov   +2 more
exaly