1 citations · 1 across the 5 of their papers we have counts for
6 papers
High-Probability Minimax Adaptive Estimation in Besov Spaces via Online-to-Batch
Paul Liautaud, Pierre Gaillard, Olivier Wintenberger
We study nonparametric regression over Besov spaces from noisy observations under sub-exponential noise, aiming to achieve minimax-optimal guarantees on the integrated squared erro…
Optimized projection-free algorithms for online learning: construction and worst-case analysis
Julien Weibel, Pierre Gaillard, Wouter M. Koolen +1
This work studies and develop projection-free algorithms for online learning with linear optimization oracles (a.k.a. Frank-Wolfe) for handling the constraint set. More precisely,…
Minimax Adaptive Online Nonparametric Regression over Besov Spaces
Paul Liautaud, Pierre Gaillard, Olivier Wintenberger
We study online adversarial regression with convex losses against a rich class of continuous yet highly irregular prediction rules, modeled by Besov spaces with general…
Minimax-optimal and Locally-adaptive Online Nonparametric Regression
Paul Liautaud, Pierre Gaillard, Olivier Wintenberger
We study adversarial online nonparametric regression with general convex losses and propose a parameter-free learning algorithm that achieves minimax optimal rates. Our approach le…
Adaptive approximation of monotone functions
Pierre Gaillard, Sébastien Gerchinovitz, Étienne de Montbrun
We study the classical problem of approximating a non-decreasing function in norm by sequentially querying its values, for known compact r…
Forecasting electricity consumption by aggregating specialized experts
Marie Devaine, Pierre Gaillard, Yannig Goude +1
We consider the setting of sequential prediction of arbitrary sequences based on specialized experts. We first provide a review of the relevant literature and present two theoretic…