Pierre Gaillard | DeepAI

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∙ 09/14/2023

Adaptive approximation of monotone functions

We study the classical problem of approximating a non-decreasing functio...

0 Pierre Gaillard, et al. ∙

∙ 02/23/2023

Sequential Counterfactual Risk Minimization

Counterfactual Risk Minimization (CRM) is a framework for dealing with t...

0 Houssam Zenati, et al. ∙

∙ 02/16/2023

A mirror descent approach for Mean Field Control applied to Demande-Side management

We consider a finite-horizon Mean Field Control problem for Markovian mo...

0 Bianca Marin Moreno, et al. ∙

∙ 02/11/2022

Efficient Kernel UCB for Contextual Bandits

In this paper, we tackle the computational efficiency of kernelized UCB ...

0 Houssam Zenati, et al. ∙

∙ 10/18/2021

Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits

In the fixed budget thresholding bandit problem, an algorithm sequential...

9 Reda Ouhamma, et al. ∙

∙ 10/08/2021

Mixability made efficient: Fast online multiclass logistic regression

Mixability has been shown to be a powerful tool to obtain algorithms wit...

0 Rémi Jézéquel, et al. ∙

∙ 06/10/2021

A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip

We introduce the continuized Nesterov acceleration, a close variant of N...

0 Mathieu Even, et al. ∙

∙ 02/11/2021

A Continuized View on Nesterov Acceleration

We introduce the "continuized" Nesterov acceleration, a close variant of...

0 Raphaël Berthier, et al. ∙

∙ 02/06/2021

Online nonparametric regression with Sobolev kernels

In this work we investigate the variation of the online kernelized ridge...

0 Oleksandr Zadorozhnyi, et al. ∙

∙ 11/13/2020

Non-stationary Online Regression

Online forecasting under a changing environment has been a problem of in...

0 Anant Raj, et al. ∙

∙ 06/15/2020

Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model

In the context of statistical supervised learning, the noiseless linear ...

0 Raphaël Berthier, et al. ∙

∙ 04/14/2020

Improved Sleeping Bandits with Stochastic Actions Sets and Adversarial Rewards

In this paper, we consider the problem of sleeping bandits with stochast...

0 Aadirupa Saha, et al. ∙

∙ 03/18/2020

Efficient improper learning for online logistic regression

We consider the setting of online logistic regression and consider the r...

0 Rémi Jézéquel, et al. ∙

∙ 03/13/2020

Experimental Comparison of Semi-parametric, Parametric, and Machine Learning Models for Time-to-Event Analysis Through the Concordance Index

In this paper, we make an experimental comparison of semi-parametric (Co...

5 Camila Fernandez, et al. ∙

∙ 02/26/2019

Efficient online learning with kernels for adversarial large scale problems

We are interested in a framework of online learning with kernels for low...

0 Rémi Jézéquel, et al. ∙

∙ 02/13/2019

Bayesian inference and non-linear extensions of the CIRCE method for quantifying the uncertainty of closure relationships integrated into thermal-hydraulic system codes

Uncertainty Quantification of closure relationships integrated into ther...

0 Guillaume Damblin, et al. ∙

∙ 01/28/2019

Target Tracking for Contextual Bandits: Application to Demand Side Management

We propose a contextual-bandit approach for demand side management by of...

0 Margaux Brégère, et al. ∙

∙ 05/29/2018

Uniform regret bounds over R^d for the sequential linear regression problem with the square loss

We consider the setting of online linear regression for arbitrary determ...

0 Pierre Gaillard, et al. ∙

∙ 05/23/2018

Efficient online algorithms for fast-rate regret bounds under sparsity

We consider the online convex optimization problem. In the setting of ar...

0 Pierre Gaillard, et al. ∙

∙ 05/22/2018

Gossip of Statistical Observations using Orthogonal Polynomials

Consider a network of agents connected by communication links, where eac...

0 Raphaël Berthier, et al. ∙

∙ 02/27/2017

Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning

We investigate contextual online learning with nonparametric (Lipschitz)...

0 Nicolò Cesa-Bianchi, et al. ∙

∙ 02/26/2015

A Chaining Algorithm for Online Nonparametric Regression

We consider the problem of online nonparametric regression with arbitrar...

0 Pierre Gaillard, et al. ∙

∙ 05/07/2014

A consistent deterministic regression tree for non-parametric prediction of time series

We study online prediction of bounded stationary ergodic processes. To d...

0 Pierre Gaillard, et al. ∙

∙ 02/10/2014

A Second-order Bound with Excess Losses

We study online aggregation of the predictions of experts, and first sho...

0 Pierre Gaillard, et al. ∙

∙ 07/09/2012

Forecasting electricity consumption by aggregating specialized experts

We consider the setting of sequential prediction of arbitrary sequences ...

0 Marie Devaine, et al. ∙

∙ 02/15/2012

Mirror Descent Meets Fixed Share (and feels no regret)

Mirror descent with an entropic regularizer is known to achieve shifting...

0 Nicolò Cesa-Bianchi, et al. ∙

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