3.4k citations · 9.9k across the 108 of their papers we have counts for
4 papers · 2 filters
Finite-Time Analysis of Kernelised Contextual Bandits
Michal Valko, Nathaniel Korda, Remi Munos +2
We tackle the problem of online reward maximisation over a large finite set of actions described by their contexts. We focus on the case when the number of actions is too big to sa…
Fast gradient descent for drifting least squares regression, with application to bandits
Nathaniel Korda, Prashanth L. A., Rémi Munos
Online learning algorithms require to often recompute least squares regression estimates of parameters. We study improving the computational complexity of such algorithms by using…
Concentration bounds for temporal difference learning with linear function approximation: The case of batch data and uniform sampling
L. A. Prashanth, Nathaniel Korda, Rémi Munos
We propose a stochastic approximation (SA) based method with randomization of samples for policy evaluation using the least squares temporal difference (LSTD) algorithm. Our propos…
Selecting the State-Representation in Reinforcement Learning
Odalric-Ambrym Maillard, Rémi Munos, Daniil Ryabko
The problem of selecting the right state-representation in a reinforcement learning problem is considered. Several models (functions mapping past observations to a finite set) of t…