16 citations · 73 across the 29 of their papers we have counts for
6 papers · 1 filter
Indexability is Not Enough for Whittle: Improved, Near-Optimal Algorithms for Restless Bandits
Abheek Ghosh, Dheeraj Nagaraj, Manish Jain +1
We study the problem of planning restless multi-armed bandits (RMABs) with multiple actions. This is a popular model for multi-agent systems with applications like multi-channel co…
Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation
Gandharv Patil, Prashanth L. A., Dheeraj Nagaraj +1
We study the finite-time behaviour of the popular temporal difference (TD) learning algorithm when combined with tail-averaging. We derive finite time bounds on the parameter error…
Multi-User Reinforcement Learning with Low Rank Rewards
Naman Agarwal, Prateek Jain, Suhas Kowshik +2
In this work, we consider the problem of collaborative multi-user reinforcement learning. In this setting there are multiple users with the same state-action space and transition p…
Metastable Mixing of Markov Chains: Efficiently Sampling Low Temperature Exponential Random Graphs
Guy Bresler, Dheeraj Nagaraj, Eshaan Nichani
In this paper we consider the problem of sampling from the low-temperature exponential random graph model (ERGM). The usual approach is via Markov chain Monte Carlo, but Bhamidi et…
Utilising the CLT Structure in Stochastic Gradient based Sampling : Improved Analysis and Faster Algorithms
Aniket Das, Dheeraj Nagaraj, Anant Raj
We consider stochastic approximations of sampling algorithms, such as Stochastic Gradient Langevin Dynamics (SGLD) and the Random Batch Method (RBM) for Interacting Particle Dynamc…
Introspective Experience Replay: Look Back When Surprised
Ramnath Kumar, Dheeraj Nagaraj
In reinforcement learning (RL), experience replay-based sampling techniques play a crucial role in promoting convergence by eliminating spurious correlations. However, widely used…