How to help seismic analysts to verify the French seismic bulletin? - David Mercier; Pierre Gaillard; Michaël Aupetit 001; Carole Maillard; Robert Quach; Jean-Denis Muller (Eng. Appl. Artif. Intell., 2006)

Apprentissage statistique de la topologie d'un ensemble de données étiquetées. - Pierre Gaillard; Michaël Aupetit 001; Gérard Govaert (EGC, 2007)

Un modèle génératif pour l'Apprentissage de la Topologie. - Michaël Aupetit 001; Pierre Gaillard; Gérard Govaert (AAFD, 2008)

Learning topology of a labeled data set with the supervised generative Gaussian graph. - Pierre Gaillard; Michaël Aupetit 001; Gérard Govaert (Neurocomputing, 2008)

Mesurer et visualiser les distorsions dans les techniques de projection continues. - Michaël Aupetit 001; Pierre Gaillard (Rev. d'Intelligence Artif., 2008)

Le Graphe Génératif Gaussien. - Pierre Gaillard; Michaël Aupetit 001; Gérard Govaert (Monde des Util. Anal. Données, 2009)

Un graphe génératif pour la classification semi-supervisée. - Pierre Gaillard; Michaël Aupetit 001; Gérard Govaert (Ingénierie des Systèmes d Inf., 2010)

Mirror Descent Meets Fixed Share (and feels no regret). - Nicolò Cesa-Bianchi; Pierre Gaillard; Gábor Lugosi; Gilles Stoltz (NIPS, 2012)

A new look at shifting regret - Nicolò Cesa-Bianchi; Pierre Gaillard; Gábor Lugosi; Gilles Stoltz (CoRR, 2012)

Forecasting electricity consumption by aggregating specialized experts - Marie Devaine; Pierre Gaillard; Yannig Goude; Gilles Stoltz (CoRR, 2012)

Forecasting electricity consumption by aggregating specialized experts - A review of the sequential aggregation of specialized experts, with an application to Slovakian and French country-wide one-day-ahead (half-)hourly predictions. - Marie Devaine; Pierre Gaillard; Yannig Goude; Gilles Stoltz (Mach. Learn., 2013)

A second-order bound with excess losses. - Pierre Gaillard; Gilles Stoltz; Tim van Erven (COLT, 2014)

A consistent deterministic regression tree for non-parametric prediction of time series. - Pierre Gaillard; Paul Baudin (CoRR, 2014)

A Chaining Algorithm for Online Nonparametric Regression. - Pierre Gaillard; Sébastien Gerchinovitz (COLT, 2015)

Association of array processing and statistical modelling for seismic event monitoring. - Paul Bui Quang; Pierre Gaillard; Yoann Cano (EUSIPCO, 2015)

Detection and classification of seismic events with progressive multi-channel correlation and hidden Markov models. - Paul Bui Quang; Pierre Gaillard; Yoann Cano; Munkhuu Ulzibat (Comput. Geosci., 2015)

Contributions à l'agrégation séquentielle robuste d'experts : Travaux sur l'erreur d'approximation et la prévision en loi. Applications à la prévision pour les marchés de l'énergie. (Contributions to online robust aggregation : work on the approximation error and on probabilistic forecasting. Applications to forecasting for energy markets). - Pierre Gaillard (2015)

Sparse Accelerated Exponential Weights. - Pierre Gaillard; Olivier Wintenberger (AISTATS, 2017)

Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning. - Nicolò Cesa-Bianchi; Pierre Gaillard; Claudio Gentile; Sébastien Gerchinovitz (COLT, 2017)

Online Nonparametric Learning, Chaining, and the Role of Partial Feedback. - Nicolò Cesa-Bianchi; Pierre Gaillard; Claudio Gentile; Sébastien Gerchinovitz (CoRR, 2017)

Efficient online algorithms for fast-rate regret bounds under sparsity. - Pierre Gaillard; Olivier Wintenberger (NeurIPS, 2018)

Gossip of Statistical Observations using Orthogonal Polynomials. - Raphaël Berthier; Francis R. Bach; Pierre Gaillard (CoRR, 2018)

Uniform regret bounds over Rd for the sequential linear regression problem with the square loss. - Pierre Gaillard; Sébastien Gerchinovitz; Malo Huard; Gilles Stoltz (ALT, 2019)

Target Tracking for Contextual Bandits: Application to Demand Side Management. - Margaux Brégère; Pierre Gaillard; Yannig Goude; Gilles Stoltz (ICML, 2019)

Efficient online learning with kernels for adversarial large scale problems. - Rémi Jézéquel; Pierre Gaillard; Alessandro Rudi (NeurIPS, 2019)

Efficient improper learning for online logistic regression. - Rémi Jézéquel; Pierre Gaillard; Alessandro Rudi (COLT, 2020)

Improved Sleeping Bandits with Stochastic Action Sets and Adversarial Rewards. - Aadirupa Saha; Pierre Gaillard; Michal Valko (ICML, 2020)

Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model. - Raphaël Berthier; Francis R. Bach; Pierre Gaillard (NeurIPS, 2020)

Experimental Comparison of Semi-parametric, Parametric, and Machine Learning Models for Time-to-Event Analysis Through the Concordance Index. - Camila Fernandez; Chung Shue Chen; Pierre Gaillard; Alonso Silva (CoRR, 2020)

Improved Sleeping Bandits with Stochastic Actions Sets and Adversarial Rewards. - Aadirupa Saha; Pierre Gaillard; Michal Valko (CoRR, 2020)

Non-stationary Online Regression. - Anant Raj; Pierre Gaillard; Christophe Saad (CoRR, 2020)

Accelerated Gossip in Networks of Given Dimension Using Jacobi Polynomial Iterations. - Raphaël Berthier; Francis R. Bach; Pierre Gaillard (SIAM J. Math. Data Sci., 2020)

Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms. - Mathieu Even; Raphaël Berthier; Francis R. Bach; Nicolas Flammarion; Hadrien Hendrikx; Pierre Gaillard; Laurent Massoulié; Adrien B. Taylor (NeurIPS, 2021)

Mixability made efficient: Fast online multiclass logistic regression. - Rémi Jézéquel; Pierre Gaillard; Alessandro Rudi (NeurIPS, 2021)

Dueling Bandits with Adversarial Sleeping. - Aadirupa Saha; Pierre Gaillard (NeurIPS, 2021)

Online nonparametric regression with Sobolev kernels. - Oleksandr Zadorozhnyi; Pierre Gaillard; Sébastien Gerchinovitz; Alessandro Rudi (CoRR, 2021)

A Continuized View on Nesterov Acceleration. - Raphaël Berthier; Francis R. Bach; Nicolas Flammarion; Pierre Gaillard; Adrien B. Taylor (CoRR, 2021)

A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip. - Mathieu Even; Raphaël Berthier; Francis R. Bach; Nicolas Flammarion; Pierre Gaillard; Hadrien Hendrikx; Laurent Massoulié; Adrien B. Taylor (CoRR, 2021)

Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits. - Reda Ouhamma; Rémy Degenne; Pierre Gaillard; Vianney Perchet (CoRR, 2021)

Efficient Kernelized UCB for Contextual Bandits. - Houssam Zenati; Alberto Bietti; Eustache Diemert; Julien Mairal; Matthieu Martin; Pierre Gaillard (AISTATS, 2022)

Versatile Dueling Bandits: Best-of-both World Analyses for Learning from Relative Preferences. - Aadirupa Saha; Pierre Gaillard (ICML, 2022)

Efficient Kernel UCB for Contextual Bandits. - Houssam Zenati; Alberto Bietti; Eustache Diemert; Julien Mairal; Matthieu Martin; Pierre Gaillard (CoRR, 2022)

Versatile Dueling Bandits: Best-of-both-World Analyses for Online Learning from Preferences. - Aadirupa Saha; Pierre Gaillard (CoRR, 2022)

One Arrow, Two Kills: An Unified Framework for Achieving Optimal Regret Guarantees in Sleeping Bandits. - Pierre Gaillard; Aadirupa Saha; Soham Dan (CoRR, 2022)

One Arrow, Two Kills: A Unified Framework for Achieving Optimal Regret Guarantees in Sleeping Bandits. - Pierre Gaillard; Aadirupa Saha; Soham Dan (AISTATS, 2023)

Strategy Repair in Reachability Games. - Pierre Gaillard; Fabio Patrizi; Giuseppe Perelli (ECAI, 2023)

Sequential Counterfactual Risk Minimization. - Houssam Zenati; Eustache Diemert; Matthieu Martin; Julien Mairal; Pierre Gaillard (ICML, 2023)

Reimagining Demand-Side Management with Mean Field Learning. - Bianca Marin Moreno; Margaux Brégère; Pierre Gaillard; Nadia Oudjane (CoRR, 2023)

Adaptive approximation of monotone functions. - Pierre Gaillard; Sébastien Gerchinovitz; Étienne de Montbrun (CoRR, 2023)

Towards Strategy Repair for Adjustable Autonomy. - Pierre Gaillard; Fabio Patrizi; Giuseppe Perelli (AAPEI@ECAI, 2024)

Efficient Model-Based Concave Utility Reinforcement Learning through Greedy Mirror Descent. - Bianca Marin Moreno; Margaux Brégère; Pierre Gaillard; Nadia Oudjane (AISTATS, 2024)

Strategy Repair for Reachability Games (short paper). - Pierre Gaillard; Fabio Patrizi; Giuseppe Perelli (ICTCS, 2024)

MetaCURL: Non-stationary Concave Utility Reinforcement Learning. - Bianca Marin Moreno; Margaux Brégère; Pierre Gaillard; Nadia Oudjane (NeurIPS, 2024)

Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits. - Julien Zhou; Pierre Gaillard; Thibaud Rahier; Houssam Zenati; Julyan Arbel (NeurIPS, 2024)

Fredholm Determinant and Wronskian Representations of the Solutions to the Schrödinger Equation with a KdV-Potential. - Pierre Gaillard (Axioms, 2024)

Online Learning Approach for Survival Analysis. - Camila Fernandez; Pierre Gaillard; Joseph De Vilmarest; Olivier Wintenberger (CoRR, 2024)

Covariance-Adaptive Least-Squares Algorithm for Stochastic Combinatorial Semi-Bandits. - Julien Zhou; Pierre Gaillard; Thibaud Rahier; Houssam Zenati; Julyan Arbel (CoRR, 2024)

Stop Relying on No-Choice and Do not Repeat the Moves: Optimal, Efficient and Practical Algorithms for Assortment Optimization. - Aadirupa Saha; Pierre Gaillard (CoRR, 2024)

Experimental Comparison of Ensemble Methods and Time-to-Event Analysis Models Through Integrated Brier Score and Concordance Index. - Camila Fernandez; Chung Shue Chen; Pierre Gaillard; Alonso Silva (CoRR, 2024)

Structured Prediction in Online Learning. - Pierre Boudart; Alessandro Rudi; Pierre Gaillard (CoRR, 2024)

Minimax-optimal and Locally-adaptive Online Nonparametric Regression. - Paul Liautaud; Pierre Gaillard; Olivier Wintenberger (ALT, 2025)

Logarithmic Regret for Unconstrained Submodular Maximization Stochastic Bandit. - Julien Zhou; Pierre Gaillard; Thibaud Rahier; Julyan Arbel (ALT, 2025)

Finally Rank-Breaking Conquers MNL Bandits: Optimal and Efficient Algorithms for MNL Assortment. - Aadirupa Saha; Pierre Gaillard (ICLR, 2025)

Counterfactual Learning of Stochastic Policies with Continuous Actions. - Houssam Zenati; Alberto Bietti; Matthieu Martin; Eustache Diemert; Pierre Gaillard; Julien Mairal (Trans. Mach. Learn. Res., 2025)

Online Episodic Convex Reinforcement Learning. - Bianca Marin Moreno; Khaled Eldowa; Pierre Gaillard; Margaux Brégère; Nadia Oudjane (CoRR, 2025)

(Online) Convex Optimization for Demand-Side Management: Application to Thermostatically Controlled Loads. - Bianca Marin Moreno; Margaux Brégère; Pierre Gaillard; Nadia Oudjane (J. Optim. Theory Appl., 2025)

Enjoying Non-linearity in Multinomial Logistic Bandits. - Pierre Boudart; Pierre Gaillard; Alessandro Rudi (CoRR, 2025)