In this work, we derive sharp non-asymptotic deviation bounds for weight...
In this paper, we propose a variance reduction approach for Markov chain...
We consider the reinforcement learning (RL) setting, in which the agent ...
In this paper, we establish novel deviation bounds for additive function...
We consider reinforcement learning in an environment modeled by an episo...
This paper provides a finite-time analysis of linear stochastic approxim...
This paper investigates the approximation properties of deep neural netw...
We propose the Bayes-UCBVI algorithm for reinforcement learning in tabul...
We develop an Explore-Exploit Markov chain Monte Carlo algorithm
(Ex^2MC...
This paper provides a non-asymptotic analysis of linear stochastic
appro...
We undertake a precise study of the non-asymptotic properties of vanilla...
This paper studies the exponential stability of random matrix products d...
Linear two-timescale stochastic approximation (SA) scheme is an importan...