Search Results for author: Nihal Sharma

Found 4 papers, 1 papers with code

Episodic Bandits with Stochastic Experts

no code implementations7 Jul 2021 Nihal Sharma, Soumya Basu, Karthikeyan Shanmugam, Sanjay Shakkottai

The agent interacts with the environment over episodes, with each episode having different context distributions; this results in the `best expert' changing across episodes.

Bandits with Mean Bounds

no code implementations19 Feb 2020 Nihal Sharma, Soumya Basu, Karthikeyan Shanmugam, Sanjay Shakkottai

In the stochastic case, we propose the non-optimistic Global Under-Explore (GLUE) algorithm which employs the inferred subgaussian estimates to adapt the rate of exploration for the arms.

Contextual Bandits with Stochastic Experts

1 code implementation23 Feb 2018 Rajat Sen, Karthikeyan Shanmugam, Nihal Sharma, Sanjay Shakkottai

We consider the problem of contextual bandits with stochastic experts, which is a variation of the traditional stochastic contextual bandit with experts problem.

Multi-Armed Bandits

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