14 citations · 15 across the 6 of their papers we have counts for
14 papers
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…
Binary input reconstruction for linear systems: a performance analysis
Sophie M. Fosson
Recovering the digital input of a time-discrete linear system from its (noisy) output is a significant challenge in the fields of data transmission, deconvolution, channel equaliza…
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…
Centralized and distributed online learning for sparse time-varying optimization
Sophie M. Fosson
The development of online algorithms to track time-varying systems has drawn a lot of attention in the last years, in particular in the framework of online convex optimization. Mea…
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…