59 citations · 93 across the 11 of their papers we have counts for
10 papers · 1 filter
Fast iterative regularization by reusing data
Cristian Vega, Cesare Molinari, Lorenzo Rosasco +1
Discrete inverse problems correspond to solving a system of equations in a stable way with respect to noise in the data. A typical approach to enforce uniqueness and select a meani…
Iterative regularization for low complexity regularizers
Cesare Molinari, Mathurin Massias, Lorenzo Rosasco +1
Iterative regularization exploits the implicit bias of an optimization algorithm to regularize ill-posed problems. Constructing algorithms with such built-in regularization mechani…
Parallel Random Block-Coordinate Forward-Backward Algorithm: A Unified Convergence Analysis
Saverio Salzo, Silvia Villa
We study the block-coordinate forward-backward algorithm in which the blocks are updated in a random and possibly parallel manner, according to arbitrary probabilities. The algorit…
Sparse Multiple Kernel Learning: Support Identification via Mirror Stratifiability
Guillaume Garrigos, Lorenzo Rosasco, Silvia Villa
In statistical machine learning, kernel methods allow to consider infinite dimensional feature spaces with a computational cost that only depends on the number of observations. Thi…
Thresholding gradient methods in Hilbert spaces: support identification and linear convergence
Guillaume Garrigos, Lorenzo Rosasco, Silvia Villa
We study regularized least squares optimization problem in a separable Hilbert space. We show that the iterative soft-thresholding algorithm (ISTA) converges linearly, wit…
Don't relax: early stopping for convex regularization
Simon Matet, Lorenzo Rosasco, Silvia Villa +1
We consider the problem of designing efficient regularization algorithms when regularization is encoded by a (strongly) convex functional. Unlike classical penalization methods bas…