55 citations · 121 across the 18 of their papers we have counts for
6 papers · 1 filter
Diversity-Preserving K-Armed Bandits, Revisited
Hédi Hadiji, Sébastien Gerchinovitz, Jean-Michel Loubes +1
We consider the bandit-based framework for diversity-preserving recommendations introduced by Celis et al. (2019), who approached it in the case of a polytope mainly by a reduction…
Uniform regret bounds over for the sequential linear regression problem with the square loss
Pierre Gaillard, Sébastien Gerchinovitz, Malo Huard +1
We consider the setting of online linear regression for arbitrary deterministic sequences, with the square loss. We are interested in the aim set by Bartlett et al. (2015): obtain…
Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning
Nicolò Cesa-Bianchi, Pierre Gaillard, Claudio Gentile +1
We investigate contextual online learning with nonparametric (Lipschitz) comparison classes under different assumptions on losses and feedback information. For full information fee…
A Chaining Algorithm for Online Nonparametric Regression
Pierre Gaillard, Sébastien Gerchinovitz
We consider the problem of online nonparametric regression with arbitrary deterministic sequences. Using ideas from the chaining technique, we design an algorithm that achieves a D…
Adaptive and optimal online linear regression on -balls
Sébastien Gerchinovitz, Jia Yuan Yu
We consider the problem of online linear regression on individual sequences. The goal in this paper is for the forecaster to output sequential predictions which are, after time…
Sparsity regret bounds for individual sequences in online linear regression
Sébastien Gerchinovitz
We consider the problem of online linear regression on arbitrary deterministic sequences when the ambient dimension d can be much larger than the number of time rounds T. We introd…