4 citations · 4 across the 4 of their papers we have counts for
4 papers
Indexability and Rollout Policy for Multi-State Partially Observable Restless Bandits
Rahul Meshram, Kesav Kaza
Restless multi-armed bandits with partially observable states has applications in communication systems, age of information and recommendation systems. In this paper, we study mult…
Monte Carlo Rollout Policy for Recommendation Systems with Dynamic User Behavior
Rahul Meshram, Kesav Kaza
We model online recommendation systems using the hidden Markov multi-state restless multi-armed bandit problem. To solve this we present Monte Carlo rollout policy. We illustrate n…
Simulation Based Algorithms for Markov Decision Processes and Multi-Action Restless Bandits
Rahul Meshram, Kesav Kaza
We consider multi-dimensional Markov decision processes and formulate a long term discounted reward optimization problem. Two simulation based algorithms---Monte Carlo rollout poli…
Online repeated posted price auctions with a demand side platform
Rahul Meshram, Kesav Kaza
We consider an online ad network problem in which an ad exchange auctions ad slots and intermediaries called demand side platforms (DSPs) buy these ad slots for their clients (adve…