François Portier

Orcid: 0000-0002-9283-3135

According to our database1, François Portier authored at least 26 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
High-dimensional nonconvex LASSO-type M-estimators.
J. Multivar. Anal., 2024

Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Sharp error bounds for imbalanced classification: how many examples in the minority class?
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Asymptotic Analysis of Conditioned Stochastic Gradient Descent.
Trans. Mach. Learn. Res., 2023

Conditional independence testing via weighted partial copulas.
J. Multivar. Anal., 2023

Scalable and hyper-parameter-free non-parametric covariate shift adaptation with conditional sampling.
CoRR, 2023

Speeding up Monte Carlo Integration: Control Neighbors for Optimal Convergence.
CoRR, 2023

On the bias of K-fold cross validation with stable learners.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
SGD with Coordinate Sampling: Theory and Practice.
J. Mach. Learn. Res., 2022

Empirical Risk Minimization under Random Censorship.
J. Mach. Learn. Res., 2022

A Quadrature Rule combining Control Variates and Adaptive Importance Sampling.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Adaptive Importance Sampling meets Mirror Descent : a Bias-variance Tradeoff.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Control variate selection for Monte Carlo integration.
Stat. Comput., 2021

High dimensional regression for regenerative time-series: An application to road traffic modeling.
Comput. Stat. Data Anal., 2021

Individual Survival Curves with Conditional Normalizing Flows.
Proceedings of the 8th IEEE International Conference on Data Science and Advanced Analytics, 2021

Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Learning methods for RSSI-based geolocation: A comparative study.
Pervasive Mob. Comput., 2020

Risk bounds when learning infinitely many response functions by ordinary linear regression.
CoRR, 2020

Towards Asymptotic Optimality with Conditioned Stochastic Gradient Descent.
CoRR, 2020

Metric Learning for Fingerprint RSSI-Localization.
Proceedings of the IEEE/ION Position, Location and Navigation Symposium, 2020

2019
Monte Carlo integration with a growing number of control variates.
J. Appl. Probab., 2019

Empirical Risk Minimization under Random Censorship: Theory and Practice.
CoRR, 2019

2018
On the weak convergence of the empirical conditional copula under a simplifying assumption.
J. Multivar. Anal., 2018

Asymptotic optimality of adaptive importance sampling.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Beating Monte Carlo Integration: a Nonasymptotic Study of Kernel Smoothing Methods.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2013
Optimal transformation: A new approach for covering the central subspace.
J. Multivar. Anal., 2013


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