Integral approximation by kernel smoothing B Delyon, F Portier | 46 | 2016 |
Asymptotic optimality of adaptive importance sampling F Portier, B Delyon Advances in neural information processing systems 31, 2018 | 44* | 2018 |
On the weak convergence of the empirical conditional copula under a simplifying assumption F Portier, J Segers Journal of Multivariate Analysis 166, 160-181, 2018 | 41 | 2018 |
Monte Carlo integration with a growing number of control variates F Portier, J Segers Journal of Applied Probability 56 (4), 1168-1186, 2019 | 32 | 2019 |
Infinite-dimensional gradient-based descent for alpha-divergence minimisation K Daudel, R Douc, F Portier The Annals of Statistics 49 (4), 2250-2270, 2021 | 24 | 2021 |
Bootstrap testing of the rank of a matrix via least-squared constrained estimation F Portier, B Delyon Journal of the American Statistical Association 109 (505), 160-172, 2014 | 20 | 2014 |
Control variate selection for Monte Carlo integration R Leluc, F Portier, J Segers Statistics and Computing 31 (4), 50, 2021 | 19 | 2021 |
Safe adaptive importance sampling: A mixture approach B Delyon, F Portier | 19 | 2021 |
Asymptotic analysis of conditioned stochastic gradient descent R Leluc, F Portier Transactions on Machine Learning Research, 2023 | 18* | 2023 |
Efficiency and bootstrap in the promotion time cure model F Portier, A El Ghouch, I Van Keilegom | 18 | 2017 |
Optimal transformation: A new approach for covering the central subspace F Portier, B Delyon Journal of Multivariate Analysis 115, 84-107, 2013 | 16 | 2013 |
Learning methods for RSSI-based geolocation: A comparative study K Elgui, P Bianchi, F Portier, O Isson Pervasive and Mobile Computing 67, 101199, 2020 | 15 | 2020 |
Empirical risk minimization under random censorship G Ausset, S Clémençon, F Portier Journal of Machine Learning Research 23 (5), 1-59, 2022 | 14* | 2022 |
Tail Inverse Regression: dimension reduction for prediction of extremes A Aghbalou, F Portier, A Sabourin, C Zhou Bernoulli 30 (1), 503-533, 2024 | 13 | 2024 |
Adaptive importance sampling meets mirror descent: a bias-variance tradeoff A Korba, F Portier International Conference on Artificial Intelligence and Statistics, 11503-11527, 2022 | 13 | 2022 |
Rademacher complexity for Markov chains: Applications to kernel smoothing and Metropolis–Hastings P Bertail, F Portier | 11 | 2019 |
Nearest neighbor empirical processes F Portier Bernoulli 31 (1), 312-332, 2025 | 10* | 2025 |
Speeding up Monte Carlo integration: Control neighbors for optimal convergence R Leluc, F Portier, J Segers, A Zhuman arXiv preprint arXiv:2305.06151, 2023 | 10 | 2023 |
Sgd with coordinate sampling: Theory and practice R Leluc, F Portier Journal of Machine Learning Research 23 (342), 1-47, 2022 | 9 | 2022 |
Risk bounds when learning infinitely many response functions by ordinary linear regression V Plassier, F Portier, J Segers Annales de l'Institut Henri Poincare (B) Probabilites et statistiques 59 (1 …, 2023 | 8 | 2023 |