15 citations · 45 across the 14 of their papers we have counts for
14 papers
El0ps: An Exact L0-regularized Problems Solver
Théo Guyard, Cédric Herzet, Clément Elvira
This paper presents El0ps, a Python toolbox providing several utilities to handle L0-regularized problems related to applications in machine learning, statistics, and signal proces…
A Generic Branch-and-Bound Algorithm for -Penalized Problems with Supplementary Material
Clément Elvira, Théo Guyard, Cédric Herzet
We present a generic Branch-and-Bound procedure designed to solve L0-penalized optimization problems. Existing approaches primarily focus on quadratic losses and construct relaxati…
A New Branch-and-Bound Pruning Framework for -Regularized Problems
Theo Guyard, Cédric Herzet, Clément Elvira +1
We consider the resolution of learning problems involving -regularization via Branch-and-Bound (BnB) algorithms. These methods explore regions of the feasible space of the…
One to beat them all: "RYU" -- a unifying framework for the construction of safe balls
Thu-Le Tran, Clément Elvira, Hong-Phuong Dang +1
In this paper, we present a new framework, called "RYU" for constructing "safe" regions -- specifically, bounded sets that are guaranteed to contain the dual solution of a target o…
Safe Peeling for L0-Regularized Least-Squares with supplementary material
Théo Guyard, Gilles Monnoyer, Clément Elvira +1
We introduce a new methodology dubbed ``safe peeling'' to accelerate the resolution of L0-regularized least-squares problems via a Branch-and-Bound (BnB) algorithm. Our procedure e…
Beyond GAP screening for Lasso by exploiting new dual cutting half-spaces with supplementary material
Thu-Le Tran, Clément Elvira, Hong-Phuong Dang +1
In this paper, we propose a novel safe screening test for Lasso. Our procedure is based on a safe region with a dome geometry and exploits a canonical representation of the set of…
Safe rules for the identification of zeros in the solutions of the SLOPE problem
Clément Elvira, Cédric Herzet
In this paper we propose a methodology to accelerate the resolution of the so-called "Sorted L-One Penalized Estimation" (SLOPE) problem. Our method leverages the concept of "safe…
Node-screening tests for L0-penalized least-squares problem with supplementary material
Théo Guyard, Cédric Herzet, Clément Elvira
We present a novel screening methodology to safely discard irrelevant nodes within a generic branch-and-bound (BnB) algorithm solving the l0-penalized least-squares problem. Our co…
Screen & Relax: Accelerating the resolution of Elastic-net by safe identification of the solution support
Théo Guyard, Cédric Herzet, Clément Elvira
In this paper, we propose a procedure to accelerate the resolution of the well-known "Elastic-Net" problem. Our procedure is based on the (partial) identification of the solution s…
Continuous dictionaries meet low-rank tensor approximations
Clement Elvira, Jeremy E. Cohen, Cedric Herzet +1
In this short paper we bridge two seemingly unrelated sparse approximation topics: continuous sparse coding and low-rank approximations. We show that for a specific choice of conti…
Safe squeezing for antisparse coding
Clément Elvira, Cédric Herzet
Spreading the information over all coefficients of a representation is a desirable property in many applications such as digital communication or machine learning. This so-called a…
When does OMP achieve exact recovery with continuous dictionaries?
Clément Elvira, Rémi Gribonval, Charles Soussen +1
This paper presents new theoretical results on sparse recovery guarantees for a greedy algorithm, Orthogonal Matching Pursuit (OMP), in the context of continuous parametric diction…
Bayesian nonparametric Principal Component Analysis
Clément Elvira, Pierre Chainais, Nicolas Dobigeon
Principal component analysis (PCA) is very popular to perform dimension reduction. The selection of the number of significant components is essential but often based on some practi…
Bayesian anti-sparse coding
Clément Elvira, Pierre Chainais, Nicolas Dobigeon
Sparse representations have proven their efficiency in solving a wide class of inverse problems encountered in signal and image processing. Conversely, enforcing the information to…