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pro vyhledávání: '"PATIL, VISHAKHA"'
We study the Improving Multi-Armed Bandit (IMAB) problem, where the reward obtained from an arm increases with the number of pulls it receives. This model provides an elegant abstraction for many real-world problems in domains such as education and e
Externí odkaz:
http://arxiv.org/abs/2208.09254
Fairness has emerged as an important concern in automated decision-making in recent years, especially when these decisions affect human welfare. In this work, we study fairness in temporally extended decision-making settings, specifically those formu
Externí odkaz:
http://arxiv.org/abs/2102.07120
Learning good interventions in a causal graph can be modelled as a stochastic multi-armed bandit problem with side-information. First, we study this problem when interventions are more expensive than observations and a budget is specified. If there a
Externí odkaz:
http://arxiv.org/abs/2012.07058
We study the Stochastic Multi-armed Bandit problem under bounded arm-memory. In this setting, the arms arrive in a stream, and the number of arms that can be stored in the memory at any time, is bounded. The decision-maker can only pull arms that are
Externí odkaz:
http://arxiv.org/abs/2012.05142
We study an interesting variant of the stochastic multi-armed bandit problem, called the Fair-SMAB problem, where each arm is required to be pulled for at least a given fraction of the total available rounds. We investigate the interplay between lear
Externí odkaz:
http://arxiv.org/abs/1907.10516
We study an interesting variant of the stochastic multi-armed bandit problem, called the Fair-SMAB problem, where each arm is required to be pulled for at least a given fraction of the total available rounds. We investigate the interplay between lear
Externí odkaz:
http://arxiv.org/abs/1905.11260
Akademický článek
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Akademický článek
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Publikováno v:
Journal of Clinical & Diagnostic Research. Dec2023, Vol. 17 Issue 12, p43-47. 5p.
Publikováno v:
Indian Journal of Dental Sciences; Oct-Dec2024, Vol. 16 Issue 4, p195-200, 6p