Stéphane Gaïffas

42 papers A* 2C 1Journal 36Unranked 3

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Robust Stochastic Optimization via Gradient Quantile Clipping. Trans. Mach. Learn. Res. Ibrahim Merad, Stéphane Gaïffas
2023	J	`jnl`	Convergence and concentration properties of constant step-size SGD through Markov chains. CoRR Ibrahim Merad, Stéphane Gaïffas
2023	A*	`conf`	Online Inventory Problems: Beyond the i.i.d. Setting with Online Convex Optimization. NeurIPS Massil Hihat, Stéphane Gaïffas, Guillaume Garrigos, Simon Bussy
2023	J	`jnl`	Online Inventory Problems: Beyond the i.i.d. Setting with Online Convex Optimization. CoRR Massil Hihat, Stéphane Gaïffas, Guillaume Garrigos, Simon Bussy
2023	J	`jnl`	Robust Methods for High-Dimensional Linear Learning. J. Mach. Learn. Res. Ibrahim Merad, Stéphane Gaïffas
2023	J	`jnl`	Robust Stochastic Optimization via Gradient Quantile Clipping. CoRR Ibrahim Merad, Stéphane Gaïffas
2023	J	`jnl`	Robust supervised learning with coordinate gradient descent. Stat. Comput. Ibrahim Merad, Stéphane Gaïffas
2023	J	`jnl`	WildWood: A New Random Forest Algorithm. IEEE Trans. Inf. Theory Stéphane Gaïffas, Ibrahim Merad, Yiyang Yu
2022	J	`jnl`	An improper estimator with optimal excess risk in misspecified density estimation and logistic regression. J. Mach. Learn. Res. Jaouad Mourtada, Stéphane Gaïffas
2022	J	`jnl`	Robust methods for high-dimensional linear learning. CoRR Ibrahim Merad, Stéphane Gaïffas
2022	J	`jnl`	Robust supervised learning with coordinate gradient descent. CoRR Stéphane Gaïffas, Ibrahim Merad
2021	C	`conf`	A Review on Contrastive Learning Methods and Applications to Roof-Type Classification on Aerial Images. IGARSS Ahmed Ben Saad, Sébastien Drouyer, Bastien Hell, Sylvain Gavoille, Stéphane Gaïffas, Gabriele Facciolo
2021	J	`jnl`	Predicting the Solar Potential of Rooftops using Image Segmentation and Structured Data. CoRR Daniel de Barros Soares, François Andrieux, Bastien Hell, Julien Lenhardt, Jordi Badosa, Sylvain Gavoille, Stéphane Gaïffas, Emmanuel Bacry
2021	J	`jnl`	WildWood: a new Random Forest algorithm. CoRR Stéphane Gaïffas, Ibrahim Merad, Yiyang Yu
2020	J	`jnl`	About contrastive unsupervised representation learning for classification and its convergence. CoRR Ibrahim Merad, Yiyang Yu, Emmanuel Bacry, Stéphane Gaïffas
2020	J	`jnl`	SCALPEL3: A scalable open-source library for healthcare claims databases. Int. J. Medical Informatics Emmanuel Bacry, Stéphane Gaïffas, Fanny Leroy, Maryan Morel, Dinh Phong Nguyen, Youcef Sebiat, Dian Sun
2020	J	`jnl`	Sparse and low-rank multivariate Hawkes processes. J. Mach. Learn. Res. Emmanuel Bacry, Martin Bompaire, Stéphane Gaïffas, Jean-François Muzy
2020	J	`jnl`	ZiMM: A deep learning model for long term and blurry relapses with non-clinical claims data. J. Biomed. Informatics Anastasiia Kabeshova, Yiyang Yu, Bertrand Lukacs, Emmanuel Bacry, Stéphane Gaïffas
2019	J	`jnl`	AMF: Aggregated Mondrian Forests for Online Learning. CoRR Jaouad Mourtada, Stéphane Gaïffas, Erwan Scornet
2019	J	`jnl`	An improper estimator with optimal excess risk in misspecified density estimation and logistic regression. CoRR Jaouad Mourtada, Stéphane Gaïffas
2019	J	`jnl`	Binarsity: a penalization for one-hot encoded features in linear supervised learning. J. Mach. Learn. Res. Mokhtar Z. Alaya, Simon Bussy, Stéphane Gaïffas, Agathe Guilloux
2019	J	`jnl`	On the optimality of the Hedge algorithm in the stochastic regime. J. Mach. Learn. Res. Jaouad Mourtada, Stéphane Gaïffas
2019	J	`jnl`	SCALPEL3: a scalable open-source library for healthcare claims databases. CoRR Emmanuel Bacry, Stéphane Gaïffas, Fanny Leroy, Maryan Morel, Dinh Phong Nguyen, Youcef Sebiat, Dian Sun
2019	J	`jnl`	Sparse inference of the drift of a high-dimensional Ornstein-Uhlenbeck process. J. Multivar. Anal. Stéphane Gaïffas, Gustaw Matulewicz
2019	J	`jnl`	ZiMM: a deep learning model for long term adverse events with non-clinical claims data. CoRR Emmanuel Bacry, Stéphane Gaïffas, Anastasiia Kabeshova, Yiyang Yu
2018	J	`jnl`	Anytime Hedge achieves optimal regret in the stochastic regime. CoRR Jaouad Mourtada, Stéphane Gaïffas
2018	J	`jnl`	Comparison of methods for early-readmission prediction in a high-dimensional heterogeneous covariates and time-to-event outcome framework. CoRR Simon Bussy, Raphaël Veil, Vincent Looten, Anita Burgun, Stéphane Gaïffas, Agathe Guilloux, Brigitte Ranque, Anne-Sophie Jannot
2018	J	`jnl`	Dual optimization for convex constrained objectives without the gradient-Lipschitz assumption. CoRR Martin Bompaire, Emmanuel Bacry, Stéphane Gaïffas
2017	A*	`conf`	Uncovering Causality from Multivariate Hawkes Integrated Cumulants. ICML Massil Achab, Emmanuel Bacry, Stéphane Gaïffas, Iacopo Mastromatteo, Jean-François Muzy
2017	J	`jnl`	Uncovering Causality from Multivariate Hawkes Integrated Cumulants. J. Mach. Learn. Res. Massil Achab, Emmanuel Bacry, Stéphane Gaïffas, Iacopo Mastromatteo, Jean-François Muzy
2017	—	`conf`	Universal consistency and minimax rates for online Mondrian Forests. NIPS Jaouad Mourtada, Stéphane Gaïffas, Erwan Scornet
2017	J	`jnl`	tick: a Python Library for Statistical Learning, with an emphasis on Hawkes Processes and Time-Dependent Models. J. Mach. Learn. Res. Emmanuel Bacry, Martin Bompaire, Philip Deegan, Stéphane Gaïffas, Søren Poulsen
2016	J	`jnl`	Uncovering Causality from Multivariate Hawkes Integrated Cumulants. CoRR Massil Achab, Emmanuel Bacry, Stéphane Gaïffas, Iacopo Mastromatteo, Jean-François Muzy
2015	J	`jnl`	Learning the Intensity of Time Events With Change-Points. IEEE Trans. Inf. Theory Mokhtar Z. Alaya, Stéphane Gaïffas, Agathe Guilloux
2015	J	`jnl`	Mean-field inference of Hawkes point processes. CoRR Emmanuel Bacry, Stéphane Gaïffas, Iacopo Mastromatteo, Jean-François Muzy
2015	J	`jnl`	SGD with Variance Reduction beyond Empirical Risk Minimization. CoRR Massil Achab, Agathe Guilloux, Stéphane Gaïffas, Emmanuel Bacry
2014	J	`jnl`	Link prediction in graphs with autoregressive features. J. Mach. Learn. Res. Emile Richard, Stéphane Gaïffas, Nicolas Vayatis
2013	—	`conf`	Learning to Target the Target: Automatic Audience Segmentation. ICDM (Workshops) Carlos Sureda Gutierrez, Elodie Prodhomme, Stéphane Gaïffas
2012	—	`conf`	Link Prediction in Graphs with Autoregressive Features. NIPS Emile Richard, Stéphane Gaïffas, Nicolas Vayatis
2011	J	`jnl`	Hyper-Sparse Optimal Aggregation. J. Mach. Learn. Res. Stéphane Gaïffas, Guillaume Lecué
2011	J	`jnl`	Sharp Oracle Inequalities for High-Dimensional Matrix Prediction. IEEE Trans. Inf. Theory Stéphane Gaïffas, Guillaume Lecué
2011	J	`jnl`	Weighted algorithms for compressed sensing and matrix completion CoRR Stéphane Gaïffas, Guillaume Lecué