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Aurghya Maiti

2 accepted papers

2022

A causal bandit approach to learning good atomic interventions in presence of unobserved confounders

UAI 2022poster

We study the problem of determining the best atomic intervention in a Causal Bayesian Network (CBN) specified only by its causal graph. We model this as a stochastic multi-armed bandit (MAB) problem with side-information, where interventions on CBN correspond to arms of the bandit instance. First, w…

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