Pierre Gaillard
Pierre Gaillard
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Additive models and robust aggregation for GEFCom2014 probabilistic electric load and electricity price forecasting
P Gaillard, Y Goude, R Nedellec
International Journal of forecasting 32 (3), 1038-1050, 2016
Forecasting electricity consumption by aggregating specialized experts
M Devaine, P Gaillard, Y Goude, G Stoltz
Machine Learning 90 (2), 231-260, 2013
A second-order bound with excess losses
P Gaillard, G Stoltz, T Van Erven
Conference on Learning Theory, 176-196, 2014
Mirror descent meets fixed share (and feels no regret)
N Cesa-Bianchi, P Gaillard, G Lugosi, G Stoltz
Advances in Neural Information Processing Systems 25, 980-988, 2012
Forecasting electricity consumption by aggregating experts; how to design a good set of experts
P Gaillard, Y Goude
Modeling and stochastic learning for forecasting in high dimensions, 95-115, 2015
Algorithmic chaining and the role of partial feedback in online nonparametric learning
N Cesa-Bianchi, P Gaillard, C Gentile, S Gerchinovitz
arXiv preprint arXiv:1702.08211, 2017
A new look at shifting regret
N Cesa-Bianchi, P Gaillard, G Lugosi, G Stoltz
arXiv preprint arXiv:1202.3323, 2012
A chaining algorithm for online nonparametric regression
P Gaillard, S Gerchinovitz
Conference on Learning Theory, 764-796, 2015
Accelerated Gossip in Networks of Given Dimension using Jacobi Polynomial Iterations
R Berthier, F Bach, P Gaillard
SIAM Journal on Mathematics of Data Science 2 (1), 24-47, 2020
Contributions ā l’agrégation séquentielle robuste d’experts: Travaux sur l’erreur d’approximation et la prévision en loi. Applications ā la prévision pour les marchés de l’énergie.
P Gaillard
Paris 11, 2015
Uniform regret bounds over for the sequential linear regression problem with the square loss
P Gaillard, S Gerchinovitz, M Huard, G Stoltz
Algorithmic Learning Theory, 404-432, 2019
Sparse accelerated exponential weights
P Gaillard, O Wintenberger
Artificial Intelligence and Statistics, 75-82, 2017
Online learning and game theory. a quick overview with recent results and applications
M Faure, P Gaillard, B Gaujal, V Perchet
ESAIM: Proceedings and Surveys 51, 246-271, 2015
A further look at the forecasting of the electricity consumption by aggregation of specialized experts
P Gaillard, Y Goude, G Stoltz
Technical report, École normale supérieure, Paris and EDF R&D, Clamart, 2011
Le Lasso, ou comment choisir parmi un grand nombre de variables ā l'aide de peu d'observations
A Ismaili, P Gaillard
Exposé de maîtrise, 2009
Target Tracking for Contextual Bandits: Application to Demand Side Management
M Brégčre, P Gaillard, Y Goude, G Stoltz
arXiv preprint arXiv:1901.09532, 2019
Efficient online learning with kernels for adversarial large scale problems
R Jézéquel, P Gaillard, A Rudi
Advances in Neural Information Processing Systems, 9432-9441, 2019
Efficient online algorithms for fast-rate regret bounds under sparsity
P Gaillard, O Wintenberger
Advances in Neural Information Processing Systems, 7026-7036, 2018
The CATHARE code condensation modelling confronted to the TOPFLOW-PTS steady-state experiments
F Moutin, P Gaillard, D Bestion, I Dor, P Germain
NURETH 16-16th International Topical Meeting on Nuclear Reactor Thermal …, 2015
Lecture Notes: Beyond Empirical Risk minimization Local Averages and K-Nearest Neighbors
A Rudi, P Gaillard
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Artiklar 1–20