François Portier

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 31

Top Topics

Stochastic Gradient Descent

Importance Sampling

Nearest Neighbour

Top Venues

J. Multivar. Anal.

J. Mach. Learn. Res.

Publications

Anass Aghbalou, Anne Sabourin, François Portier
Sharp error bounds for imbalanced classification: how many examples in the minority class? AISTATS (2024)
Jad Beyhum, François Portier
High-dimensional nonconvex LASSO-type M-estimators. J. Multivar. Anal. 202 (2024)
Rémi Leluc, Aymeric Dieuleveut, François Portier, Johan Segers, Aigerim Zhuman
Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates. CoRR (2024)
Pascal Bianchi, Kevin Elgui, François Portier
Conditional independence testing via weighted partial copulas. J. Multivar. Anal. 193 (2023)
François Portier, Lionel Truquet, Ikko Yamane
Scalable and hyper-parameter-free non-parametric covariate shift adaptation with conditional sampling. CoRR (2023)
Anass Aghbalou, François Portier, Anne Sabourin
Sharp error bounds for imbalanced classification: how many examples in the minority class? CoRR (2023)
Rémi Leluc, François Portier, Johan Segers, Aigerim Zhuman
Speeding up Monte Carlo Integration: Control Neighbors for Optimal Convergence. CoRR (2023)
Rémi Leluc, François Portier
Asymptotic Analysis of Conditioned Stochastic Gradient Descent. Trans. Mach. Learn. Res. 2023 (2023)
Anass Aghbalou, Anne Sabourin, François Portier
On the bias of K-fold cross validation with stable learners. AISTATS (2023)
Rémi Leluc, François Portier, Johan Segers, Aigerim Zhuman
A Quadrature Rule combining Control Variates and Adaptive Importance Sampling. CoRR (2022)
Anna Korba, François Portier
Adaptive Importance Sampling meets Mirror Descent : a Bias-variance Tradeoff. AISTATS (2022)
Rémi Leluc, François Portier
SGD with Coordinate Sampling: Theory and Practice. J. Mach. Learn. Res. 23 (2022)
Rémi Leluc, François Portier, Johan Segers, Aigerim Zhuman
A Quadrature Rule combining Control Variates and Adaptive Importance Sampling. NeurIPS (2022)
Guillaume Ausset, Stéphan Clémençon, François Portier
Empirical Risk Minimization under Random Censorship. J. Mach. Learn. Res. 23 (2022)
Rémi Leluc, François Portier, Johan Segers
Control variate selection for Monte Carlo integration. Stat. Comput. 31 (4) (2021)
Guillaume Ausset, Stéphan Clémençon, François Portier
Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications. AISTATS (2021)
Guillaume Ausset, Tom Ciffreo, François Portier, Stéphan Clémençon, Timothée Papin
Individual Survival Curves with Conditional Normalizing Flows. DSAA (2021)
Mohammed Lamine Bouchouia, François Portier
High dimensional regression for regenerative time-series: An application to road traffic modeling. Comput. Stat. Data Anal. 158 (2021)
Guillaume Ausset, Tom Ciffreo, François Portier, Stéphan Clémençon, Timothée Papin
Individual Survival Curves with Conditional Normalizing Flows. CoRR (2021)
Rémi Leluc, François Portier
SGD with Coordinate Sampling: Theory and Practice. CoRR (2021)
Kevin Elgui, Pascal Bianchi, Olivier Isson, François Portier, Renaud Marty
Metric Learning for Fingerprint RSSI-Localization. PLANS (2020)
Kevin Elgui, Pascal Bianchi, François Portier, Olivier Isson
Learning methods for RSSI-based geolocation: A comparative study. Pervasive Mob. Comput. 67 (2020)
Guillaume Ausset, Stéphan Clémençon, François Portier
Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications. CoRR (2020)
Vincent Plassier, François Portier, Johan Segers
Risk bounds when learning infinitely many response functions by ordinary linear regression. CoRR (2020)
Rémi Leluc, François Portier
Towards Asymptotic Optimality with Conditioned Stochastic Gradient Descent. CoRR (2020)
Kevin Elgui, Pascal Bianchi, François Portier, Olivier Isson
Learning Methods for RSSI-based Geolocation: A Comparative Study. EUSIPCO (2019)
François Portier, Johan Segers
Monte Carlo integration with a growing number of control variates. J. Appl. Probab. 56 (4) (2019)
Guillaume Ausset, Stéphan Clémençon, François Portier
Empirical Risk Minimization under Random Censorship: Theory and Practice. CoRR (2019)
Stéphan Clémençon, François Portier
Beating Monte Carlo Integration: a Nonasymptotic Study of Kernel Smoothing Methods. AISTATS (2018)
François Portier, Johan Segers
On the weak convergence of the empirical conditional copula under a simplifying assumption. J. Multivar. Anal. 166 (2018)
François Portier, Bernard Delyon
Asymptotic optimality of adaptive importance sampling. NeurIPS (2018)
François Portier, Bernard Delyon
Optimal transformation: A new approach for covering the central subspace. J. Multivar. Anal. 115 (2013)