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09/14/2023
Adaptive approximation of monotone functions
We study the classical problem of approximating a non-decreasing functio...
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02/23/2023
Sequential Counterfactual Risk Minimization
Counterfactual Risk Minimization (CRM) is a framework for dealing with t...
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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...
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02/11/2022
Efficient Kernel UCB for Contextual Bandits
In this paper, we tackle the computational efficiency of kernelized UCB ...
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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...
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10/08/2021
Mixability made efficient: Fast online multiclass logistic regression
Mixability has been shown to be a powerful tool to obtain algorithms wit...
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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...
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02/11/2021
A Continuized View on Nesterov Acceleration
We introduce the "continuized" Nesterov acceleration, a close variant of...
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02/06/2021
Online nonparametric regression with Sobolev kernels
In this work we investigate the variation of the online kernelized ridge...
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11/13/2020
Non-stationary Online Regression
Online forecasting under a changing environment has been a problem of in...
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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 ...
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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...
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03/18/2020
Efficient improper learning for online logistic regression
We consider the setting of online logistic regression and consider the r...
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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...
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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...
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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...
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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...
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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...
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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...
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05/22/2018
Gossip of Statistical Observations using Orthogonal Polynomials
Consider a network of agents connected by communication links, where eac...
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02/27/2017
Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning
We investigate contextual online learning with nonparametric (Lipschitz)...
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02/26/2015
A Chaining Algorithm for Online Nonparametric Regression
We consider the problem of online nonparametric regression with arbitrar...
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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...
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02/10/2014
A Second-order Bound with Excess Losses
We study online aggregation of the predictions of experts, and first sho...
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07/09/2012
Forecasting electricity consumption by aggregating specialized experts
We consider the setting of sequential prediction of arbitrary sequences ...
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02/15/2012
