2 citations · 3 across the 3 of their papers we have counts for
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eess.SY2018
Sequential Decision Making with Limited Observation Capability: Application to Wireless Networks
Kesav Kaza, Rahul Meshram, Varun Mehta +1
This work studies a generalized class of restless multi-armed bandits with hidden states and allow cumulative feedback, as opposed to the conventional instantaneous feedback. We ca…
eess.SY2017★ 2 cited
A Hidden Markov Restless Multi-armed Bandit Model for Playout Recommendation Systems
Rahul Meshram, Aditya Gopalan, D. Manjunath
We consider a restless multi-armed bandit (RMAB) in which there are two types of arms, say A and B. Each arm can be in one of two states, say or Playing a type A arm bring…
eess.SY2016
On the Whittle Index for Restless Multi-armed Hidden Markov Bandits
Rahul Meshram, D. Manjunath, Aditya Gopalan
We consider a restless multi-armed bandit in which each arm can be in one of two states. When an arm is sampled, the state of the arm is not available to the sampler. Instead, a bi…