4 papers
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…
Sparse linear regression with compressed and low-precision data via concave quadratic programming
Vito Cerone, Sophie M. Fosson, Diego Regruto
We consider the problem of the recovery of a k-sparse vector from compressed linear measurements when data are corrupted by a quantization noise. When the number of measurements is…
A linear programming approach to sparse linear regression with quantized data
Vito Cerone, Sophie M. Fosson, Diego Regruto
The sparse linear regression problem is difficult to handle with usual sparse optimization models when both predictors and measurements are either quantized or represented in low-p…