3 papers
math.PR2026
Rates of Convergence in the Central Limit Theorem for Markov Chains, with an Application to TD Learning
R. Srikant
We prove a non-asymptotic central limit theorem for vector-valued martingale differences using Stein's method, and use Poisson's equation to extend the result to functions of Marko…
cs.LG2025
Scalable Policy-Based RL Algorithms for POMDPs
Ameya Anjarlekar, Rasoul Etesami, R Srikant
The continuous nature of belief states in POMDPs presents significant computational challenges in learning the optimal policy. In this paper, we consider an approach that solves a…
cs.LG2024
Striking a Balance: An Optimal Mechanism Design for Heterogenous Differentially Private Data Acquisition for Logistic Regression
Ameya Anjarlekar, Rasoul Etesami, R. Srikant
We address the challenge of solving machine learning tasks using data from privacy-sensitive sellers. Since the data is private, we design a data market that incentivizes sellers t…