Stéphane Gaïffas

Publication Activity (10 Years)

Years Active: 2011-2023
Publications (10 Years): 35

Top Topics

Variance Reduction

Empirical Risk Minimization

Online Convex Optimization

Top Venues

J. Mach. Learn. Res.

IEEE Trans. Inf. Theory

Int. J. Medical Informatics

Publications

Massil Hihat, Stéphane Gaïffas, Guillaume Garrigos, Simon Bussy
Online Inventory Problems: Beyond the i.i.d. Setting with Online Convex Optimization. NeurIPS (2023)
Massil Hihat, Stéphane Gaïffas, Guillaume Garrigos, Simon Bussy
Online Inventory Problems: Beyond the i.i.d. Setting with Online Convex Optimization. CoRR (2023)
Ibrahim Merad, Stéphane Gaïffas
Robust supervised learning with coordinate gradient descent. Stat. Comput. 33 (5) (2023)
Ibrahim Merad, Stéphane Gaïffas
Convergence and concentration properties of constant step-size SGD through Markov chains. CoRR (2023)
Ibrahim Merad, Stéphane Gaïffas
Robust Stochastic Optimization via Gradient Quantile Clipping. CoRR (2023)
Stéphane Gaïffas, Ibrahim Merad, Yiyang Yu
WildWood: A New Random Forest Algorithm. IEEE Trans. Inf. Theory 69 (10) (2023)
Ibrahim Merad, Stéphane Gaïffas
Robust Methods for High-Dimensional Linear Learning. J. Mach. Learn. Res. 24 (2023)
Jaouad Mourtada, Stéphane Gaïffas
An improper estimator with optimal excess risk in misspecified density estimation and logistic regression. J. Mach. Learn. Res. 23 (2022)
Ibrahim Merad, Stéphane Gaïffas
Robust methods for high-dimensional linear learning. CoRR (2022)
Stéphane Gaïffas, Ibrahim Merad
Robust supervised learning with coordinate gradient descent. CoRR (2022)
Stéphane Gaïffas, Ibrahim Merad, Yiyang Yu
WildWood: a new Random Forest algorithm. CoRR (2021)
Ahmed Ben Saad, Sébastien Drouyer, Bastien Hell, Sylvain Gavoille, Stéphane Gaïffas, Gabriele Facciolo
A Review on Contrastive Learning Methods and Applications to Roof-Type Classification on Aerial Images. IGARSS (2021)
Daniel de Barros Soares, François Andrieux, Bastien Hell, Julien Lenhardt, Jordi Badosa, Sylvain Gavoille, Stéphane Gaïffas, Emmanuel Bacry
Predicting the Solar Potential of Rooftops using Image Segmentation and Structured Data. CoRR (2021)
Emmanuel Bacry, Stéphane Gaïffas, Fanny Leroy, Maryan Morel, Dinh Phong Nguyen, Youcef Sebiat, Dian Sun
SCALPEL3: A scalable open-source library for healthcare claims databases. Int. J. Medical Informatics 141 (2020)
Emmanuel Bacry, Martin Bompaire, Stéphane Gaïffas, Jean-François Muzy
Sparse and low-rank multivariate Hawkes processes. J. Mach. Learn. Res. 21 (2020)
Ibrahim Merad, Yiyang Yu, Emmanuel Bacry, Stéphane Gaïffas
About contrastive unsupervised representation learning for classification and its convergence. CoRR (2020)
Anastasiia Kabeshova, Yiyang Yu, Bertrand Lukacs, Emmanuel Bacry, Stéphane Gaïffas
ZiMM: A deep learning model for long term and blurry relapses with non-clinical claims data. J. Biomed. Informatics 110 (2020)
Jaouad Mourtada, Stéphane Gaïffas
An improper estimator with optimal excess risk in misspecified density estimation and logistic regression. CoRR (2019)
Emmanuel Bacry, Stéphane Gaïffas, Fanny Leroy, Maryan Morel, Dinh Phong Nguyen, Youcef Sebiat, Dian Sun
SCALPEL3: a scalable open-source library for healthcare claims databases. CoRR (2019)
Jaouad Mourtada, Stéphane Gaïffas
On the optimality of the Hedge algorithm in the stochastic regime. J. Mach. Learn. Res. 20 (2019)
Jaouad Mourtada, Stéphane Gaïffas, Erwan Scornet
AMF: Aggregated Mondrian Forests for Online Learning. CoRR (2019)
Stéphane Gaïffas, Gustaw Matulewicz
Sparse inference of the drift of a high-dimensional Ornstein-Uhlenbeck process. J. Multivar. Anal. 169 (2019)
Emmanuel Bacry, Stéphane Gaïffas, Anastasiia Kabeshova, Yiyang Yu
ZiMM: a deep learning model for long term adverse events with non-clinical claims data. CoRR (2019)
Mokhtar Z. Alaya, Simon Bussy, Stéphane Gaïffas, Agathe Guilloux
Binarsity: a penalization for one-hot encoded features in linear supervised learning. J. Mach. Learn. Res. 20 (2019)
Martin Bompaire, Emmanuel Bacry, Stéphane Gaïffas
Dual optimization for convex constrained objectives without the gradient-Lipschitz assumption. CoRR (2018)
Simon Bussy, Raphaël Veil, Vincent Looten, Anita Burgun, Stéphane Gaïffas, Agathe Guilloux, Brigitte Ranque, Anne-Sophie Jannot
Comparison of methods for early-readmission prediction in a high-dimensional heterogeneous covariates and time-to-event outcome framework. CoRR (2018)
Jaouad Mourtada, Stéphane Gaïffas
Anytime Hedge achieves optimal regret in the stochastic regime. CoRR (2018)
Massil Achab, Emmanuel Bacry, Stéphane Gaïffas, Iacopo Mastromatteo, Jean-François Muzy
Uncovering Causality from Multivariate Hawkes Integrated Cumulants. J. Mach. Learn. Res. 18 (2017)
Massil Achab, Emmanuel Bacry, Stéphane Gaïffas, Iacopo Mastromatteo, Jean-François Muzy
Uncovering Causality from Multivariate Hawkes Integrated Cumulants. ICML (2017)
Jaouad Mourtada, Stéphane Gaïffas, Erwan Scornet
Universal consistency and minimax rates for online Mondrian Forests. NIPS (2017)
Emmanuel Bacry, Martin Bompaire, Philip Deegan, Stéphane Gaïffas, Søren Poulsen
tick: a Python Library for Statistical Learning, with an emphasis on Hawkes Processes and Time-Dependent Models. J. Mach. Learn. Res. 18 (2017)
Massil Achab, Emmanuel Bacry, Stéphane Gaïffas, Iacopo Mastromatteo, Jean-François Muzy
Uncovering Causality from Multivariate Hawkes Integrated Cumulants. CoRR (2016)
Massil Achab, Agathe Guilloux, Stéphane Gaïffas, Emmanuel Bacry
SGD with Variance Reduction beyond Empirical Risk Minimization. CoRR (2015)
Emmanuel Bacry, Stéphane Gaïffas, Iacopo Mastromatteo, Jean-François Muzy
Mean-field inference of Hawkes point processes. CoRR (2015)
Mokhtar Z. Alaya, Stéphane Gaïffas, Agathe Guilloux
Learning the Intensity of Time Events With Change-Points. IEEE Trans. Inf. Theory 61 (9) (2015)
Emile Richard, Stéphane Gaïffas, Nicolas Vayatis
Link prediction in graphs with autoregressive features. J. Mach. Learn. Res. 15 (1) (2014)
Carlos Sureda Gutierrez, Elodie Prodhomme, Stéphane Gaïffas
Learning to Target the Target: Automatic Audience Segmentation. ICDM (Workshops) (2013)
Emile Richard, Stéphane Gaïffas, Nicolas Vayatis
Link Prediction in Graphs with Autoregressive Features. NIPS (2012)
Stéphane Gaïffas, Guillaume Lecué
Sharp Oracle Inequalities for High-Dimensional Matrix Prediction. IEEE Trans. Inf. Theory 57 (10) (2011)
Stéphane Gaïffas, Guillaume Lecué
Weighted algorithms for compressed sensing and matrix completion CoRR (2011)
Stéphane Gaïffas, Guillaume Lecué
Hyper-Sparse Optimal Aggregation. J. Mach. Learn. Res. 12 (2011)