
Optimal minibatch and step sizes for SAGA
Recently it has been shown that the step sizes of a family of variance r...
01/31/2019 ∙ by Nidham Gazagnadou, et al. ∙ 22 ∙ shareread it

Screening Rules for Lasso with NonConvex Sparse Regularizers
Leveraging on the convexity of the Lasso problem , screening rules help ...
02/16/2019 ∙ by Alain Rakotomamonjy, et al. ∙ 18 ∙ shareread it

Concomitant Lasso with Repetitions (CLaR): beyond averaging multiple realizations of heteroscedastic noise
Sparsity promoting norms are frequently used in high dimensional regress...
02/07/2019 ∙ by Quentin Bertrand, et al. ∙ 18 ∙ shareread it

Dual Extrapolation for Sparse Generalized Linear Models
Generalized Linear Models (GLM) form a wide class of regression and clas...
07/12/2019 ∙ by Mathurin Massias, et al. ∙ 11 ∙ shareread it

Generalized Concomitant MultiTask Lasso for sparse multimodal regression
In high dimension, it is customary to consider Lassotype estimators to ...
05/27/2017 ∙ by Mathurin Massias, et al. ∙ 0 ∙ shareread it

From safe screening rules to working sets for faster Lassotype solvers
Convex sparsitypromoting regularizations are ubiquitous in modern stati...
03/21/2017 ∙ by Mathurin Massias, et al. ∙ 0 ∙ shareread it

On the benefits of output sparsity for multilabel classification
The multilabel classification framework, where each observation can be ...
03/14/2017 ∙ by Evgenii Chzhen, et al. ∙ 0 ∙ shareread it

Gap Safe screening rules for sparsity enforcing penalties
In high dimensional regression settings, sparsity enforcing penalties ha...
11/17/2016 ∙ by Eugene Ndiaye, et al. ∙ 0 ∙ shareread it

Efficient Smoothed Concomitant Lasso Estimation for High Dimensional Regression
In high dimensional settings, sparse structures are crucial for efficien...
06/08/2016 ∙ by Eugene Ndiaye, et al. ∙ 0 ∙ shareread it

Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions
In decentralized networks (of sensors, connected objects, etc.), there i...
06/08/2016 ∙ by Igor Colin, et al. ∙ 0 ∙ shareread it

GAP Safe Screening Rules for SparseGroupLasso
In high dimensional settings, sparse structures are crucial for efficien...
02/19/2016 ∙ by Eugene Ndiaye, et al. ∙ 0 ∙ shareread it

Extending Gossip Algorithms to Distributed Estimation of UStatistics
Efficient and robust algorithms for decentralized estimation in networks...
11/17/2015 ∙ by Igor Colin, et al. ∙ 0 ∙ shareread it

GAP Safe screening rules for sparse multitask and multiclass models
High dimensional regression benefits from sparsity promoting regularizat...
06/11/2015 ∙ by Eugene Ndiaye, et al. ∙ 0 ∙ shareread it

Mind the duality gap: safer rules for the Lasso
Screening rules allow to early discard irrelevant variables from the opt...
05/13/2015 ∙ by Olivier Fercoq, et al. ∙ 0 ∙ shareread it

Learning Heteroscedastic Models by Convex Programming under Group Sparsity
Popular sparse estimation methods based on ℓ_1relaxation, such as the L...
04/16/2013 ∙ by Arnak S. Dalalyan, et al. ∙ 0 ∙ shareread it

A twostage denoising filter: the preprocessed Yaroslavsky filter
This paper describes a simple image noise removal method which combines ...
08/31/2012 ∙ by Joseph Salmon, et al. ∙ 0 ∙ shareread it

Poisson noise reduction with nonlocal PCA
Photonlimited imaging arises when the number of photons collected by a ...
06/02/2012 ∙ by Joseph Salmon, et al. ∙ 0 ∙ shareread it

Oracle inequalities and minimax rates for nonlocal means and related adaptive kernelbased methods
This paper describes a novel theoretical characterization of the perform...
12/19/2011 ∙ by Ery AriasCastro, et al. ∙ 0 ∙ shareread it

A hierarchical Bayesian perspective on majorizationminimization for nonconvex sparse regression: application to M/EEG source imaging
Majorizationminimization (MM) is a standard iterative optimization tech...
10/24/2017 ∙ by Yousra Bekhti, et al. ∙ 0 ∙ shareread it

Statistical Inference with Ensemble of Clustered Desparsified Lasso
Medical imaging involves highdimensional data, yet their acquisition is...
06/15/2018 ∙ by JérômeAlexis Chevalier, et al. ∙ 0 ∙ shareread it

Safe Grid Search with Optimal Complexity
Popular machine learning estimators involve regularization parameters th...
10/12/2018 ∙ by Eugene Ndiaye, et al. ∙ 0 ∙ shareread it
Joseph Salmon
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Assistant Professor at TELECOM ParisTech, Associate member at INRIA Parietal, Visiting assistant professor at UW, Statistics departement.