8 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…
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…
Enhancing low-rank solutions in semidefinite relaxations of Boolean quadratic problems
V. Cerone, S. M. Fosson, D. Regruto
Boolean quadratic optimization problems occur in a number of applications. Their mixed integer-continuous nature is challenging, since it is inherently NP-hard. For this motivation…