217 citations · 568 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
Thompson Sampling for 1-Dimensional Exponential Family Bandits
Nathaniel Korda, Emilie Kaufmann, Remi Munos
Thompson Sampling has been demonstrated in many complex bandit models, however the theoretical guarantees available for the parametric multi-armed bandit are still limited to the B…
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…