353 citations · 1.8k across the 69 of their papers we have counts for
7 papers · 1 filter
Dynamic Screening: Accelerating First-Order Algorithms for the Lasso and Group-Lasso
Antoine Bonnefoy, Valentin Emiya, Liva Ralaivola +1
Recent computational strategies based on screening tests have been proposed to accelerate algorithms addressing penalized sparse regression problems such as the Lasso. Such approac…
Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14)
L. Jacques, C. De Vleeschouwer, Y. Boursier +64
The implicit objective of the biennial "international - Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST) is to foster collaboration between interna…
Sparse and spurious: dictionary learning with noise and outliers
Rémi Gribonval, Rodolphe Jenatton, Francis Bach
A popular approach within the signal processing and machine learning communities consists in modelling signals as sparse linear combinations of atoms selected from a learned dictio…
Separable Cosparse Analysis Operator Learning
Matthias Seibert, Julian Wörmann, Rémi Gribonval +1
The ability of having a sparse representation for a certain class of signals has many applications in data analysis, image processing, and other research fields. Among sparse repre…
Learning computationally efficient dictionaries and their implementation as fast transforms
Luc Le Magoarou, Rémi Gribonval
Dictionary learning is a branch of signal processing and machine learning that aims at finding a frame (called dictionary) in which some training data admits a sparse representatio…
On The Sample Complexity of Sparse Dictionary Learning
Matthias Seibert, Martin Kleinsteuber, Rémi Gribonval +2
In the synthesis model signals are represented as a sparse combinations of atoms from a dictionary. Dictionary learning describes the acquisition process of the underlying dictiona…
Balancing Sparsity and Rank Constraints in Quadratic Basis Pursuit
Cagdas Bilen, Gilles Puy, Rémi Gribonval +1
We investigate the methods that simultaneously enforce sparsity and low-rank structure in a matrix as often employed for sparse phase retrieval problems or phase calibration proble…