Pierre Gaillard
Orcid: 0000-0002-7073-8284
According to our database1,
Pierre Gaillard
authored at least 60 papers
between 2006 and 2024.
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Bibliography
2024
CoRR, 2024
Experimental Comparison of Ensemble Methods and Time-to-Event Analysis Models Through Integrated Brier Score and Concordance Index.
CoRR, 2024
Stop Relying on No-Choice and Do not Repeat the Moves: Optimal, Efficient and Practical Algorithms for Assortment Optimization.
CoRR, 2024
Covariance-Adaptive Least-Squares Algorithm for Stochastic Combinatorial Semi-Bandits.
CoRR, 2024
Fredholm Determinant and Wronskian Representations of the Solutions to the Schrödinger Equation with a KdV-Potential.
Axioms, 2024
Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Proceedings of the 25th Italian Conference on Theoretical Computer Science, 2024
Efficient Model-Based Concave Utility Reinforcement Learning through Greedy Mirror Descent.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023
One Arrow, Two Kills: A Unified Framework for Achieving Optimal Regret Guarantees in Sleeping Bandits.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
2022
One Arrow, Two Kills: An Unified Framework for Achieving Optimal Regret Guarantees in Sleeping Bandits.
CoRR, 2022
Versatile Dueling Bandits: Best-of-both-World Analyses for Online Learning from Preferences.
CoRR, 2022
Versatile Dueling Bandits: Best-of-both World Analyses for Learning from Relative Preferences.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
2021
Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits.
CoRR, 2021
A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip.
CoRR, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
2020
Accelerated Gossip in Networks of Given Dimension Using Jacobi Polynomial Iterations.
SIAM J. Math. Data Sci., 2020
CoRR, 2020
Experimental Comparison of Semi-parametric, Parametric, and Machine Learning Models for Time-to-Event Analysis Through the Concordance Index.
CoRR, 2020
Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the Conference on Learning Theory, 2020
2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Uniform regret bounds over R<sup>d</sup> for the sequential linear regression problem with the square loss.
Proceedings of the Algorithmic Learning Theory, 2019
2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
2017
CoRR, 2017
Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning.
Proceedings of the 30th Conference on Learning Theory, 2017
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
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).
PhD thesis, 2015
Detection and classification of seismic events with progressive multi-channel correlation and hidden Markov models.
Comput. Geosci., 2015
Association of array processing and statistical modelling for seismic event monitoring.
Proceedings of the 23rd European Signal Processing Conference, 2015
Proceedings of The 28th Conference on Learning Theory, 2015
2014
A consistent deterministic regression tree for non-parametric prediction of time series.
CoRR, 2014
Proceedings of The 27th Conference on Learning Theory, 2014
2013
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., 2013
2012
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012
2010
Ingénierie des Systèmes d Inf., 2010
2009
2008
Rev. d'Intelligence Artif., 2008
Learning topology of a labeled data set with the supervised generative Gaussian graph.
Neurocomputing, 2008
Proceedings of the Apprentissage Artificiel et Fouille de Données, 2008
2007
Proceedings of the Extraction et gestion des connaissances (EGC'2007), 2007
2006
Eng. Appl. Artif. Intell., 2006