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ORCIDFrançois Portier
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2020 – today
- 2024
[j11]Jad Beyhum, François Portier:
High-dimensional nonconvex LASSO-type M-estimators. J. Multivar. Anal. 202: 105303 (2024)- [c11]Anass Aghbalou, Anne Sabourin, François Portier:
Sharp error bounds for imbalanced classification: how many examples in the minority class? AISTATS 2024: 838-846 - [c10]Rémi Leluc, Aymeric Dieuleveut, François Portier, Johan Segers, Aigerim Zhuman:
Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates. ICML 2024 - [i11]Rémi Leluc, Aymeric Dieuleveut, François Portier, Johan Segers, Aigerim Zhuman:
Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates. CoRR abs/2402.01493 (2024) - 2023
- [j10]Pascal Bianchi, Kevin Elgui, François Portier:
Conditional independence testing via weighted partial copulas. J. Multivar. Anal. 193: 105120 (2023) - [j9]Rémi Leluc, François Portier:
Asymptotic Analysis of Conditioned Stochastic Gradient Descent. Trans. Mach. Learn. Res. 2023 (2023) - [c9]Anass Aghbalou, Anne Sabourin, François Portier:
On the bias of K-fold cross validation with stable learners. AISTATS 2023: 3775-3794 - [i10]Rémi Leluc, François Portier, Johan Segers, Aigerim Zhuman:
Speeding up Monte Carlo Integration: Control Neighbors for Optimal Convergence. CoRR abs/2305.06151 (2023) - [i9]Anass Aghbalou, François Portier, Anne Sabourin:
Sharp error bounds for imbalanced classification: how many examples in the minority class? CoRR abs/2310.14826 (2023) - [i8]François Portier, Lionel Truquet, Ikko Yamane:
Scalable and hyper-parameter-free non-parametric covariate shift adaptation with conditional sampling. CoRR abs/2312.09969 (2023) - 2022
- [j8]Guillaume Ausset, Stéphan Clémençon, François Portier:
Empirical Risk Minimization under Random Censorship. J. Mach. Learn. Res. 23: 5:1-5:59 (2022) - [j7]Rémi Leluc
, François Portier:
SGD with Coordinate Sampling: Theory and Practice. J. Mach. Learn. Res. 23: 342:1-342:47 (2022) - [c8]Anna Korba, François Portier:
Adaptive Importance Sampling meets Mirror Descent : a Bias-variance Tradeoff. AISTATS 2022: 11503-11527 - [c7]Rémi Leluc, François Portier, Johan Segers, Aigerim Zhuman:
A Quadrature Rule combining Control Variates and Adaptive Importance Sampling. NeurIPS 2022 - [i7]Rémi Leluc, François Portier, Johan Segers, Aigerim Zhuman:
A Quadrature Rule combining Control Variates and Adaptive Importance Sampling. CoRR abs/2205.11890 (2022) - 2021
- [j6]Mohammed Lamine Bouchouia, François Portier:
High dimensional regression for regenerative time-series: An application to road traffic modeling. Comput. Stat. Data Anal. 158: 107191 (2021) - [j5]Rémi Leluc, François Portier, Johan Segers:
Control variate selection for Monte Carlo integration. Stat. Comput. 31(4): 50 (2021) - [c6]Guillaume Ausset, Stéphan Clémençon, François Portier:
Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications. AISTATS 2021: 532-540 - [c5]Guillaume Ausset, Tom Ciffreo, François Portier, Stéphan Clémençon, Timothée Papin:
Individual Survival Curves with Conditional Normalizing Flows. DSAA 2021: 1-10 - [i6]Rémi Leluc, François Portier:
SGD with Coordinate Sampling: Theory and Practice. CoRR abs/2105.11818 (2021) - [i5]Guillaume Ausset, Tom Ciffreo, François Portier, Stéphan Clémençon, Timothée Papin:
Individual Survival Curves with Conditional Normalizing Flows. CoRR abs/2107.12825 (2021) - 2020
- [j4]Kevin Elgui, Pascal Bianchi, François Portier, Olivier Isson:
Learning methods for RSSI-based geolocation: A comparative study. Pervasive Mob. Comput. 67: 101199 (2020) - [c4]Kevin Elgui, Pascal Bianchi, Olivier Isson, François Portier, Renaud Marty:
Metric Learning for Fingerprint RSSI-Localization. PLANS 2020: 1036-1042 - [i4]Rémi Leluc, François Portier:
Towards Asymptotic Optimality with Conditioned Stochastic Gradient Descent. CoRR abs/2006.02745 (2020) - [i3]Vincent Plassier, François Portier, Johan Segers:
Risk bounds when learning infinitely many response functions by ordinary linear regression. CoRR abs/2006.09223 (2020) - [i2]Guillaume Ausset, Stéphan Clémençon, François Portier:
Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications. CoRR abs/2006.15043 (2020)
2010 – 2019
- 2019
- [j3]François Portier, Johan Segers:
Monte Carlo integration with a growing number of control variates. J. Appl. Probab. 56(4): 1168-1186 (2019) - [c3]Kevin Elgui, Pascal Bianchi, François Portier, Olivier Isson:
Learning Methods for RSSI-based Geolocation: A Comparative Study. EUSIPCO 2019: 1-5 - [i1]Guillaume Ausset, Stéphan Clémençon, François Portier:
Empirical Risk Minimization under Random Censorship: Theory and Practice. CoRR abs/1906.01908 (2019) - 2018
- [j2]François Portier, Johan Segers:
On the weak convergence of the empirical conditional copula under a simplifying assumption. J. Multivar. Anal. 166: 160-181 (2018) - [c2]Stéphan Clémençon, François Portier:
Beating Monte Carlo Integration: a Nonasymptotic Study of Kernel Smoothing Methods. AISTATS 2018: 548-556 - [c1]François Portier, Bernard Delyon:
Asymptotic optimality of adaptive importance sampling. NeurIPS 2018: 3138-3148 - 2013
- [j1]François Portier, Bernard Delyon:
Optimal transformation: A new approach for covering the central subspace. J. Multivar. Anal. 115: 84-107 (2013)
Coauthor Index
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last updated on 2024-09-13 00:42 CEST by the dblp team
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