10 citations · 11 across the 2 of their papers we have counts for
2 papers
cs.AI2016★ 1 cited
Random Shuffling and Resets for the Non-stationary Stochastic Bandit Problem
Robin Allesiardo, Raphaël Féraud, Odalric-Ambrym Maillard
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…
cs.NE2014★ 10 cited
A Neural Networks Committee for the Contextual Bandit Problem
Robin Allesiardo, Raphael Feraud, Djallel Bouneffouf
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…