1 citations · 1 across the 6 of their papers we have counts for
9 papers · 1 filter
Sparse learning with concave regularization: relaxation of the irrepresentable condition
V. Cerone, S. M. Fosson, D. Regruto +1
Learning sparse models from data is an important task in all those frameworks where relevant information should be identified within a large dataset. This can be achieved by formul…
Alternating direction method of multipliers for polynomial optimization
V. Cerone, S. M. Fosson, S. Pirrera +1
Multivariate polynomial optimization is a prevalent model for a number of engineering problems. From a mathematical viewpoint, polynomial optimization is challenging because it is…
Fast sparse optimization via adaptive shrinkage
Vito Cerone, Sophie M. Fosson, Diego Regruto
The need for fast sparse optimization is emerging, e.g., to deal with large-dimensional data-driven problems and to track time-varying systems. In the framework of linear sparse op…
A feedback control approach to convex optimization with inequality constraints
V. Cerone, S. M. Fosson, S. Pirrera +1
We propose a novel continuous-time algorithm for inequality-constrained convex optimization inspired by proportional-integral control. Unlike the popular primal-dual gradient dynam…
A convex optimization approach to online set-membership EIV identification of LTV systems
Sophie M. Fosson, Diego Regruto, Talal Abdalla +1
This paper addresses the problem of recursive set-membership identification for linear time varying (LTV) systems when both input and output measurements are affected by bounded ad…
Sparse linear regression from perturbed data
S. M. Fosson, V. Cerone, D. Regruto
The problem of sparse linear regression is relevant in the context of linear system identification from large datasets. When data are collected from real-world experiments, measure…