Stéphane Gaïffas

According to our database, Stéphane Gaïffas authored at least 32 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

WildWood: A New Random Forest Algorithm.

Stéphane Gaïffas, Ibrahim Merad, Yiyang Yu

IEEE Trans. Inf. Theory, October, 2023

Robust supervised learning with coordinate gradient descent.

Ibrahim Merad, Stéphane Gaïffas

Stat. Comput., October, 2023

Robust Methods for High-Dimensional Linear Learning.

Ibrahim Merad, Stéphane Gaïffas

J. Mach. Learn. Res., 2023

Robust Stochastic Optimization via Gradient Quantile Clipping.

Ibrahim Merad, Stéphane Gaïffas

CoRR, 2023

Convergence and concentration properties of constant step-size SGD through Markov chains.

Ibrahim Merad, Stéphane Gaïffas

CoRR, 2023

Online Inventory Problems: Beyond the i.i.d. Setting with Online Convex Optimization.

Massil Hihat, Stéphane Gaïffas, Guillaume Garrigos, Simon Bussy

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

An improper estimator with optimal excess risk in misspecified density estimation and logistic regression.

Jaouad Mourtada, Stéphane Gaïffas

J. Mach. Learn. Res., 2022

2021

Predicting the Solar Potential of Rooftops using Image Segmentation and Structured Data.

Daniel de Barros Soares, François Andrieux, Bastien Hell, Julien Lenhardt, Jordi Badosa, Sylvain Gavoille, Stéphane Gaïffas, Emmanuel Bacry

CoRR, 2021

A Review on Contrastive Learning Methods and Applications to Roof-Type Classification on Aerial Images.

Ahmed Ben Saad, Sébastien Drouyer, Bastien Hell, Sylvain Gavoille, Stéphane Gaïffas, Gabriele Facciolo

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

2020

Sparse and low-rank multivariate Hawkes processes.

Emmanuel Bacry, Martin Bompaire, Stéphane Gaïffas, Jean-François Muzy

J. Mach. Learn. Res., 2020

ZiMM: A deep learning model for long term and blurry relapses with non-clinical claims data.

Anastasiia Kabeshova, Yiyang Yu, Bertrand Lukacs, Emmanuel Bacry, Stéphane Gaïffas

J. Biomed. Informatics, 2020

SCALPEL3: A scalable open-source library for healthcare claims databases.

Emmanuel Bacry, Stéphane Gaïffas, Fanny Leroy, Maryan Morel, Dinh Phong Nguyen, Youcef Sebiat, Dian Sun

Int. J. Medical Informatics, 2020

About contrastive unsupervised representation learning for classification and its convergence.

Ibrahim Merad, Yiyang Yu, Emmanuel Bacry, Stéphane Gaïffas

CoRR, 2020

2019

Sparse inference of the drift of a high-dimensional Ornstein-Uhlenbeck process.

Stéphane Gaïffas, Gustaw Matulewicz

J. Multivar. Anal., 2019

On the optimality of the Hedge algorithm in the stochastic regime.

Jaouad Mourtada, Stéphane Gaïffas

J. Mach. Learn. Res., 2019

Binarsity: a penalization for one-hot encoded features in linear supervised learning.

Mokhtar Z. Alaya, Simon Bussy, Stéphane Gaïffas, Agathe Guilloux

J. Mach. Learn. Res., 2019

ZiMM: a deep learning model for long term adverse events with non-clinical claims data.

Emmanuel Bacry, Stéphane Gaïffas, Anastasiia Kabeshova, Yiyang Yu

CoRR, 2019

AMF: Aggregated Mondrian Forests for Online Learning.

Jaouad Mourtada, Stéphane Gaïffas, Erwan Scornet

CoRR, 2019

2018

Anytime Hedge achieves optimal regret in the stochastic regime.

Jaouad Mourtada, Stéphane Gaïffas

CoRR, 2018

Comparison of methods for early-readmission prediction in a high-dimensional heterogeneous covariates and time-to-event outcome framework.

Simon Bussy, Raphaël Veil, Vincent Looten, Anita Burgun, Stéphane Gaïffas, Agathe Guilloux, Brigitte Ranque, Anne-Sophie Jannot

CoRR, 2018

Dual optimization for convex constrained objectives without the gradient-Lipschitz assumption.

Martin Bompaire, Emmanuel Bacry, Stéphane Gaïffas

CoRR, 2018

2017

tick: a Python Library for Statistical Learning, with an emphasis on Hawkes Processes and Time-Dependent Models.

Emmanuel Bacry, Martin Bompaire, Philip Deegan, Stéphane Gaïffas, Søren Poulsen

J. Mach. Learn. Res., 2017

Uncovering Causality from Multivariate Hawkes Integrated Cumulants.

Massil Achab, Emmanuel Bacry, Stéphane Gaïffas, Iacopo Mastromatteo, Jean-François Muzy

J. Mach. Learn. Res., 2017

Universal consistency and minimax rates for online Mondrian Forests.

Jaouad Mourtada, Stéphane Gaïffas, Erwan Scornet

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2015

Learning the Intensity of Time Events With Change-Points.

Mokhtar Z. Alaya, Stéphane Gaïffas, Agathe Guilloux

IEEE Trans. Inf. Theory, 2015

Mean-field inference of Hawkes point processes.

Emmanuel Bacry, Stéphane Gaïffas, Iacopo Mastromatteo, Jean-François Muzy

CoRR, 2015

SGD with Variance Reduction beyond Empirical Risk Minimization.

Massil Achab, Agathe Guilloux, Stéphane Gaïffas, Emmanuel Bacry

CoRR, 2015

2014

Link prediction in graphs with autoregressive features.

Emile Richard, Stéphane Gaïffas, Nicolas Vayatis

J. Mach. Learn. Res., 2014

2013

Learning to Target the Target: Automatic Audience Segmentation.

Carlos Sureda Gutierrez, Elodie Prodhomme, Stéphane Gaïffas

Proceedings of the Advances in Data Mining, 13th Industrial Conference, 2013

2011

Sharp Oracle Inequalities for High-Dimensional Matrix Prediction.

Stéphane Gaïffas, Guillaume Lecué

IEEE Trans. Inf. Theory, 2011

Hyper-Sparse Optimal Aggregation.

Stéphane Gaïffas, Guillaume Lecué

J. Mach. Learn. Res., 2011

Weighted algorithms for compressed sensing and matrix completion

Stéphane Gaïffas, Guillaume Lecué

CoRR, 2011