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
276 2016 A second-order bound with excess losses P Gaillard, G Stoltz, T Van Erven
Conference on Learning Theory, 176-196, 2014
184 2014 Forecasting electricity consumption by aggregating specialized experts: A review of the sequential aggregation of specialized experts, with an application to Slovakian and … M Devaine, P Gaillard, Y Goude, G Stoltz
Machine Learning 90, 231-260, 2013
129 2013 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, 2012
103 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
70 2015 Algorithmic chaining and the role of partial feedback in online nonparametric learning N Cesa-Bianchi, P Gaillard, C Gentile, S Gerchinovitz
Conference on Learning Theory, 465-481, 2017
52 2017 Tight nonparametric convergence rates for stochastic gradient descent under the noiseless linear model R Berthier, F Bach, P Gaillard
Advances in Neural Information Processing Systems 33, 2576-2586, 2020
49 2020 A chaining algorithm for online nonparametric regression P Gaillard, S Gerchinovitz
Conference on Learning Theory, 764-796, 2015
48 2015 Continuized accelerations of deterministic and stochastic gradient descents, and of gossip algorithms M Even, R Berthier, F Bach, N Flammarion, H Hendrikx, P Gaillard, ...
Advances in Neural Information Processing Systems 34, 28054-28066, 2021
45 * 2021 opera: Online prediction by expert aggregation P Gaillard, Y Goude
URL: https://CRAN. R-project. org/package= opera. r package version 1, 2016
44 * 2016 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
41 2020 A new look at shifting regret N Cesa-Bianchi, P Gaillard, G Lugosi, G Stoltz
arXiv preprint arXiv:1202.3323, 2012
32 2012 Versatile dueling bandits: Best-of-both world analyses for learning from relative preferences A Saha, P Gaillard
International Conference on Machine Learning, 19011-19026, 2022
29 * 2022 Efficient improper learning for online logistic regression R Jézéquel, P Gaillard, A Rudi
Conference on Learning Theory, 2085-2108, 2020
29 2020 Uniform regret bounds over P Gaillard, S Gerchinovitz, M Huard, G Stoltz
Algorithmic Learning Theory, 404-432, 2019
26 2019 Improved sleeping bandits with stochastic action sets and adversarial rewards A Saha, P Gaillard, M Valko
International Conference on Machine Learning, 8357-8366, 2020
25 2020 Efficient kernelized ucb for contextual bandits H Zenati, A Bietti, E Diemert, J Mairal, M Martin, P Gaillard
International Conference on Artificial Intelligence and Statistics, 5689-5720, 2022
20 2022 Efficient online learning with kernels for adversarial large scale problems R Jézéquel, P Gaillard, A Rudi
Advances in Neural Information Processing Systems 32, 2019
17 2019 Target tracking for contextual bandits: Application to demand side management M Brégère, P Gaillard, Y Goude, G Stoltz
International Conference on Machine Learning, 754-763, 2019
15 2019 Efficient and near-optimal online portfolio selection R Jézéquel, DM Ostrovskii, P Gaillard
14 2022 
Yannig GoudeEDF R&D, LMO Université Paris-SaclayEmail verificata su edf.fr