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cs.LG2024★ 1 cited
Causal Contextual Bandits with Adaptive Context
Rahul Madhavan, Aurghya Maiti, Gaurav Sinha +1
We study a variant of causal contextual bandits where the context is chosen based on an initial intervention chosen by the learner. At the beginning of each round, the learner sele…
cs.LG2024
Generalized Linear Bandits with Limited Adaptivity
Ayush Sawarni, Nirjhar Das, Siddharth Barman +1
We study the generalized linear contextual bandit problem within the constraints of limited adaptivity. In this paper, we present two algorithms, and $\texttt{R…
cs.LG2023
Nash Regret Guarantees for Linear Bandits
Ayush Sawarni, Soumybrata Pal, Siddharth Barman
We obtain essentially tight upper bounds for a strengthened notion of regret in the stochastic linear bandits framework. The strengthening -- referred to as Nash regret -- is defin…