10 citations · 11 across the 3 of their papers we have counts for
3 papers
Random Shuffling and Resets for the Non-stationary Stochastic Bandit Problem
Robin Allesiardo, Elys Allesiardo, Raphaël Féraud +1
We consider a non-stationary formulation of the stochastic multi-armed bandit where the rewards are no longer assumed to be identically distributed. For the best-arm identification…
Random Forest for the Contextual Bandit Problem - extended version
Raphaël Féraud, Robin Allesiardo, Elys Allesiardo +2
To address the contextual bandit problem, we propose an online random forest algorithm. The analysis of the proposed algorithm is based on the sample complexity needed to find the…
A Neural Networks Committee for the Contextual Bandit Problem
Robin Allesiardo, Elys Allesiardo, Raphael Feraud +1
This paper presents a new contextual bandit algorithm, NeuralBandit, which does not need hypothesis on stationarity of contexts and rewards. Several neural networks are trained to…