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2020 – today
- 2024
[j9]Pierre Gaillard
:
Fredholm Determinant and Wronskian Representations of the Solutions to the Schrödinger Equation with a KdV-Potential. Axioms 13(10): 712 (2024)- [c26]Bianca Marin Moreno, Margaux Brégère, Pierre Gaillard, Nadia Oudjane:
Efficient Model-Based Concave Utility Reinforcement Learning through Greedy Mirror Descent. AISTATS 2024: 2206-2214 - [c25]Pierre Gaillard, Fabio Patrizi, Giuseppe Perelli:
Strategy Repair for Reachability Games (short paper). ICTCS 2024: 200-205 - [i34]Camila Fernandez, Pierre Gaillard, Joseph De Vilmarest, Olivier Wintenberger:
Online Learning Approach for Survival Analysis. CoRR abs/2402.05145 (2024) - [i33]Julien Zhou, Pierre Gaillard, Thibaud Rahier, Houssam Zenati, Julyan Arbel:
Covariance-Adaptive Least-Squares Algorithm for Stochastic Combinatorial Semi-Bandits. CoRR abs/2402.15171 (2024) - [i32]Aadirupa Saha, Pierre Gaillard:
Stop Relying on No-Choice and Do not Repeat the Moves: Optimal, Efficient and Practical Algorithms for Assortment Optimization. CoRR abs/2402.18917 (2024) - [i31]Camila Fernandez, Chung Shue Chen, Pierre Gaillard, Alonso Silva:
Experimental Comparison of Ensemble Methods and Time-to-Event Analysis Models Through Integrated Brier Score and Concordance Index. CoRR abs/2403.07460 (2024) - [i30]Bianca Marin Moreno, Margaux Brégère, Pierre Gaillard, Nadia Oudjane:
MetaCURL: Non-stationary Concave Utility Reinforcement Learning. CoRR abs/2405.19807 (2024) - [i29]Pierre Boudart, Alessandro Rudi, Pierre Gaillard:
Structured Prediction in Online Learning. CoRR abs/2406.12366 (2024) - 2023
- [c24]Pierre Gaillard, Aadirupa Saha, Soham Dan:
One Arrow, Two Kills: A Unified Framework for Achieving Optimal Regret Guarantees in Sleeping Bandits. AISTATS 2023: 7755-7773 - [c23]Pierre Gaillard, Fabio Patrizi, Giuseppe Perelli:
Strategy Repair in Reachability Games. ECAI 2023: 780-787 - [c22]Houssam Zenati, Eustache Diemert, Matthieu Martin, Julien Mairal, Pierre Gaillard:
Sequential Counterfactual Risk Minimization. ICML 2023: 40681-40706 - [i28]Bianca Marin Moreno, Margaux Brégère, Pierre Gaillard, Nadia Oudjane:
Reimagining Demand-Side Management with Mean Field Learning. CoRR abs/2302.08190 (2023) - [i27]Houssam Zenati, Eustache Diemert, Matthieu Martin, Julien Mairal, Pierre Gaillard:
Sequential Counterfactual Risk Minimization. CoRR abs/2302.12120 (2023) - [i26]Pierre Gaillard, Sébastien Gerchinovitz, Étienne de Montbrun:
Adaptive approximation of monotone functions. CoRR abs/2309.07530 (2023) - 2022
- [c21]Houssam Zenati, Alberto Bietti, Eustache Diemert, Julien Mairal, Matthieu Martin, Pierre Gaillard:
Efficient Kernelized UCB for Contextual Bandits. AISTATS 2022: 5689-5720 - [c20]Aadirupa Saha, Pierre Gaillard:
Versatile Dueling Bandits: Best-of-both World Analyses for Learning from Relative Preferences. ICML 2022: 19011-19026 - [i25]Houssam Zenati, Alberto Bietti, Eustache Diemert, Julien Mairal, Matthieu Martin, Pierre Gaillard:
Efficient Kernel UCB for Contextual Bandits. CoRR abs/2202.05638 (2022) - [i24]Aadirupa Saha, Pierre Gaillard:
Versatile Dueling Bandits: Best-of-both-World Analyses for Online Learning from Preferences. CoRR abs/2202.06694 (2022) - [i23]Pierre Gaillard, Aadirupa Saha, Soham Dan:
One Arrow, Two Kills: An Unified Framework for Achieving Optimal Regret Guarantees in Sleeping Bandits. CoRR abs/2210.14998 (2022) - 2021
- [c19]Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi:
Mixability made efficient: Fast online multiclass logistic regression. NeurIPS 2021: 23692-23702 - [c18]Aadirupa Saha, Pierre Gaillard:
Dueling Bandits with Adversarial Sleeping. NeurIPS 2021: 27761-27771 - [c17]Mathieu Even, Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Hadrien Hendrikx, Pierre Gaillard, Laurent Massoulié, Adrien B. Taylor:
Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms. NeurIPS 2021: 28054-28066 - [i22]Oleksandr Zadorozhnyi, Pierre Gaillard, Sébastien Gerchinovitz, Alessandro Rudi:
Online nonparametric regression with Sobolev kernels. CoRR abs/2102.03594 (2021) - [i21]Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Pierre Gaillard, Adrien B. Taylor:
A Continuized View on Nesterov Acceleration. CoRR abs/2102.06035 (2021) - [i20]Mathieu Even, Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Pierre Gaillard, Hadrien Hendrikx, Laurent Massoulié, Adrien B. Taylor:
A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip. CoRR abs/2106.07644 (2021) - [i19]Aadirupa Saha, Pierre Gaillard:
Dueling Bandits with Adversarial Sleeping. CoRR abs/2107.02274 (2021) - [i18]Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi:
Mixability made efficient: Fast online multiclass logistic regression. CoRR abs/2110.03960 (2021) - [i17]Reda Ouhamma, Rémy Degenne, Pierre Gaillard, Vianney Perchet:
Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits. CoRR abs/2110.09133 (2021) - 2020
- [j8]Raphaël Berthier, Francis R. Bach, Pierre Gaillard:
Accelerated Gossip in Networks of Given Dimension Using Jacobi Polynomial Iterations. SIAM J. Math. Data Sci. 2(1): 24-47 (2020) - [c16]Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi:
Efficient improper learning for online logistic regression. COLT 2020: 2085-2108 - [c15]Aadirupa Saha, Pierre Gaillard, Michal Valko:
Improved Sleeping Bandits with Stochastic Action Sets and Adversarial Rewards. ICML 2020: 8357-8366 - [c14]Raphaël Berthier, Francis R. Bach, Pierre Gaillard:
Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model. NeurIPS 2020 - [i16]Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi:
Efficient improper learning for online logistic regression. CoRR abs/2003.08109 (2020) - [i15]Camila Fernandez, Chung Shue Chen, Pierre Gaillard, Alonso Silva:
Experimental Comparison of Semi-parametric, Parametric, and Machine Learning Models for Time-to-Event Analysis Through the Concordance Index. CoRR abs/2003.08820 (2020) - [i14]Aadirupa Saha, Pierre Gaillard, Michal Valko:
Improved Sleeping Bandits with Stochastic Actions Sets and Adversarial Rewards. CoRR abs/2004.06248 (2020) - [i13]Raphaël Berthier, Francis R. Bach, Pierre Gaillard:
Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model. CoRR abs/2006.08212 (2020) - [i12]Anant Raj, Pierre Gaillard, Christophe Saad:
Non-stationary Online Regression. CoRR abs/2011.06957 (2020)
2010 – 2019
- 2019
- [c13]Pierre Gaillard, Sébastien Gerchinovitz, Malo Huard, Gilles Stoltz:
Uniform regret bounds over Rd for the sequential linear regression problem with the square loss. ALT 2019: 404-432 - [c12]Margaux Brégère, Pierre Gaillard, Yannig Goude, Gilles Stoltz:
Target Tracking for Contextual Bandits: Application to Demand Side Management. ICML 2019: 754-763 - [c11]Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi:
Efficient online learning with kernels for adversarial large scale problems. NeurIPS 2019: 9427-9436 - [i11]Margaux Brégère, Pierre Gaillard, Yannig Goude, Gilles Stoltz:
Target Tracking for Contextual Bandits: Application to Demand Side Management. CoRR abs/1901.09532 (2019) - [i10]Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi:
Efficient online learning with kernels for adversarial large scale problems. CoRR abs/1902.09917 (2019) - 2018
- [c10]Pierre Gaillard, Olivier Wintenberger:
Efficient online algorithms for fast-rate regret bounds under sparsity. NeurIPS 2018: 7026-7036 - [i9]Raphaël Berthier, Francis R. Bach, Pierre Gaillard:
Gossip of Statistical Observations using Orthogonal Polynomials. CoRR abs/1805.08531 (2018) - [i8]Pierre Gaillard, Olivier Wintenberger:
Efficient online algorithms for fast-rate regret bounds under sparsity. CoRR abs/1805.09174 (2018) - [i7]Pierre Gaillard, Sébastien Gerchinovitz, Malo Huard, Gilles Stoltz:
Uniform regret bounds over Rd for the sequential linear regression problem with the square loss. CoRR abs/1805.11386 (2018) - 2017
- [c9]Pierre Gaillard, Olivier Wintenberger:
Sparse Accelerated Exponential Weights. AISTATS 2017: 75-82 - [c8]Nicolò Cesa-Bianchi, Pierre Gaillard, Claudio Gentile, Sébastien Gerchinovitz:
Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning. COLT 2017: 465-481 - [i6]Nicolò Cesa-Bianchi, Pierre Gaillard, Claudio Gentile, Sébastien Gerchinovitz:
Online Nonparametric Learning, Chaining, and the Role of Partial Feedback. CoRR abs/1702.08211 (2017) - 2015
- [b1]Pierre Gaillard:
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). University of Paris-Sud, Orsay, France, 2015 - [j7]Paul Bui Quang, Pierre Gaillard, Yoann Cano, Munkhuu Ulzibat:
Detection and classification of seismic events with progressive multi-channel correlation and hidden Markov models. Comput. Geosci. 83: 110-119 (2015) - [c7]Pierre Gaillard, Sébastien Gerchinovitz:
A Chaining Algorithm for Online Nonparametric Regression. COLT 2015: 764-796 - [c6]Paul Bui Quang, Pierre Gaillard, Yoann Cano:
Association of array processing and statistical modelling for seismic event monitoring. EUSIPCO 2015: 1945-1949 - [i5]Pierre Gaillard, Sébastien Gerchinovitz:
A Chaining Algorithm for Online Nonparametric Regression. CoRR abs/1502.07697 (2015) - 2014
- [c5]Pierre Gaillard, Gilles Stoltz, Tim van Erven:
A second-order bound with excess losses. COLT 2014: 176-196 - [i4]Pierre Gaillard, Gilles Stoltz, Tim van Erven:
A Second-order Bound with Excess Losses. CoRR abs/1402.2044 (2014) - [i3]Pierre Gaillard, Paul Baudin:
A consistent deterministic regression tree for non-parametric prediction of time series. CoRR abs/1405.1533 (2014) - 2013
- [j6]Marie Devaine, Pierre Gaillard, Yannig Goude, Gilles Stoltz:
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. Mach. Learn. 90(2): 231-260 (2013) - 2012
- [c4]Nicolò Cesa-Bianchi, Pierre Gaillard, Gábor Lugosi, Gilles Stoltz:
Mirror Descent Meets Fixed Share (and feels no regret). NIPS 2012: 989-997 - [i2]Nicolò Cesa-Bianchi, Pierre Gaillard, Gábor Lugosi, Gilles Stoltz:
A new look at shifting regret. CoRR abs/1202.3323 (2012) - [i1]Marie Devaine, Pierre Gaillard, Yannig Goude, Gilles Stoltz:
Forecasting electricity consumption by aggregating specialized experts. CoRR abs/1207.1965 (2012) - 2010
- [j5]Pierre Gaillard, Michaël Aupetit, Gérard Govaert:
Un graphe génératif pour la classification semi-supervisée. Ingénierie des Systèmes d Inf. 15(2): 97-119 (2010)
2000 – 2009
- 2009
- [j4]Pierre Gaillard, Michaël Aupetit, Gérard Govaert:
Le Graphe Génératif Gaussien. Monde des Util. Anal. Données 40: 103-120 (2009) - 2008
- [j3]Pierre Gaillard, Michaël Aupetit, Gérard Govaert:
Learning topology of a labeled data set with the supervised generative Gaussian graph. Neurocomputing 71(7-9): 1283-1299 (2008) - [j2]Michaël Aupetit, Pierre Gaillard:
Mesurer et visualiser les distorsions dans les techniques de projection continues. Rev. d'Intelligence Artif. 22(3-4): 443-472 (2008) - [c3]Michaël Aupetit, Pierre Gaillard, Gérard Govaert:
Un modèle génératif pour l'Apprentissage de la Topologie. AAFD 2008: 49-76 - 2007
- [c2]Pierre Gaillard, Michaël Aupetit, Gérard Govaert:
Learning topology of a labeled data set with the supervised generative gaussian graph. ESANN 2007: 235-240 - [c1]Pierre Gaillard, Michaël Aupetit, Gérard Govaert:
Apprentissage statistique de la topologie d'un ensemble de données étiquetées. EGC 2007: 455-460 - 2006
- [j1]David Mercier, Pierre Gaillard, Michaël Aupetit, Carole Maillard, Robert Quach, Jean-Denis Muller:
How to help seismic analysts to verify the French seismic bulletin? Eng. Appl. Artif. Intell. 19(7): 797-806 (2006)
Coauthor Index
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