3 citations · 4 across the 2 of their papers we have counts for
3 papers
cs.LG2022★ 1 cited
ProtoBandit: Efficient Prototype Selection via Multi-Armed Bandits
Arghya Roy Chaudhuri, Pratik Jawanpuria, Bamdev Mishra
In this work, we propose a multi-armed bandit-based framework for identifying a compact set of informative data instances (i.e., the prototypes) from a source dataset that best…
cs.LG2019
Regret Minimisation in Multi-Armed Bandits Using Bounded Arm Memory
Arghya Roy Chaudhuri, Shivaram Kalyanakrishnan
In this paper, we propose a constant word (RAM model) algorithm for regret minimisation for both finite and infinite Stochastic Multi-Armed Bandit (MAB) instances. Most of the exis…
cs.LG2019★ 3 cited
PAC Identification of Many Good Arms in Stochastic Multi-Armed Bandits
Arghya Roy Chaudhuri, Shivaram Kalyanakrishnan
We consider the problem of identifying any out of the best arms in an -armed stochastic multi-armed bandit. Framed in the PAC setting, this particular problem generalise…