57 citations · 120 across the 41 of their papers we have counts for
41 papers
One Arrow, Two Kills: An Unified Framework for Achieving Optimal Regret Guarantees in Sleeping Bandits
Pierre Gaillard, Aadirupa Saha, Soham Dan
We address the problem of \emph{`Internal Regret'} in \emph{Sleeping Bandits} in the fully adversarial setup, as well as draw connections between different existing notions of slee…
Efficient and Near-Optimal Online Portfolio Selection
Rémi Jézéquel, Dmitrii M. Ostrovskii, Pierre Gaillard
In the problem of online portfolio selection as formulated by Cover (1991), the trader repeatedly distributes her capital over assets in each of rounds, with the go…
Versatile Dueling Bandits: Best-of-both-World Analyses for Online Learning from Preferences
Aadirupa Saha, Pierre Gaillard
We study the problem of -armed dueling bandit for both stochastic and adversarial environments, where the goal of the learner is to aggregate information through relative prefer…
Efficient Kernel UCB for Contextual Bandits
Houssam Zenati, Alberto Bietti, Eustache Diemert +3
In this paper, we tackle the computational efficiency of kernelized UCB algorithms in contextual bandits. While standard methods require a O(CT^3) complexity where T is the horizon…
Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits
Reda Ouhamma, Rémy Degenne, Pierre Gaillard +1
In the fixed budget thresholding bandit problem, an algorithm sequentially allocates a budgeted number of samples to different distributions. It then predicts whether the mean of e…
Mixability made efficient: Fast online multiclass logistic regression
Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi
Mixability has been shown to be a powerful tool to obtain algorithms with optimal regret. However, the resulting methods often suffer from high computational complexity which has r…