255 citations · 2.4k across the 127 of their papers we have counts for
5 papers · 1 filter
On Minimax Optimal Offline Policy Evaluation
Lihong Li, Remi Munos, Csaba Szepesvari
This paper studies the off-policy evaluation problem, where one aims to estimate the value of a target policy based on a sample of observations collected by another policy. We firs…
Adaptive Monte Carlo via Bandit Allocation
James Neufeld, András György, Dale Schuurmans +1
We consider the problem of sequentially choosing between a set of unbiased Monte Carlo estimators to minimize the mean-squared-error (MSE) of a final combined estimate. By reducing…
Dyna-Style Planning with Linear Function Approximation and Prioritized Sweeping
Richard S. Sutton, Csaba Szepesvari, Alborz Geramifard +1
We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available after…
Speeding Up Planning in Markov Decision Processes via Automatically Constructed Abstractions
Alejandro Isaza, Csaba Szepesvari, Vadim Bulitko +1
In this paper, we consider planning in stochastic shortest path (SSP) problems, a subclass of Markov Decision Problems (MDP). We focus on medium-size problems whose state space can…
Online Least Squares Estimation with Self-Normalized Processes: An Application to Bandit Problems
Yasin Abbasi-Yadkori, David Pal, Csaba Szepesvari
The analysis of online least squares estimation is at the heart of many stochastic sequential decision making problems. We employ tools from the self-normalized processes to provid…