{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/105019"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/105019","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Multi-armed bandits and applications to large datasets","abstract":"This thesis considers the multi-armed bandit (MAB) problem, both the traditional bandit feedback and graphical bandits when there is side information. Motivated by the Boltzmann exploration algorithm often used in the more general context of reinforcement learning, we present Almost Boltzmann Exploration (ABE) which fixes the under-exploration issue while maintaining an expression similar to Boltzmann exploration. We then present some real world applications of the MAB framework, comparing the performance of ABE with other bandit algorithms on real world datasets.","abstract_html":"This thesis considers the multi-armed bandit (MAB) problem, both the traditional bandit feedback and graphical bandits when there is side information. Motivated by the Boltzmann exploration algorithm often used in the more general context of reinforcement learning, we present Almost Boltzmann Exploration (ABE) which fixes the under-exploration issue while maintaining an expression similar to Boltzmann exploration. 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Motivated by the Boltzmann exploration algorithm often used in the more general context of reinforcement learning, we present Almost Boltzmann Exploration (ABE) which fixes the under-exploration issue while maintaining an expression similar to Boltzmann exploration. We then present some real world applications of the MAB framework, comparing the performance of ABE with other bandit algorithms on real world datasets.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2021-05-01","The student, Seo Taek Kong, accepted the attached license on 2019-04-12 at 19:06.","The student, Seo Taek Kong, submitted this Thesis for approval on 2019-04-12 at 19:11.","This Thesis was approved for publication on 2019-04-15 at 11:16.","DSpace SAF Submission Ingestion Package generated from Vireo submission #13604 on 2019-08-22 at 15:06:13","Made available in DSpace on 2019-08-23T20:35:53Z (GMT). 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