Dec 2, 2011 · This paper studies the problem of accurately recovering a sparse vector \beta^{\star} from highly corrupted linear measurements.

Abstract—This paper studies the problem of accurately recov- ering a -sparse vector from highly corrupted linear measurements. , where is a sparse.

Abstract. This paper studies the problem of accurately recovering a sparse vector β⋆ β ⋆ from highly corrupted linear measurements y=Xβ⋆+e⋆+w y = X β ⋆ + e ⋆ + ...

This paper studies the problem of accurately recovering a sparse vector β? from highly corrupted linear measurements y = Xβ? + e? + w where e? is a sparse.

Dec 6, 2011 · Abstract—This paper studies the problem of accurately re- covering a sparse vector β* from highly corrupted linear mea-.

This paper studies the problem of accurately recovering a sparse vector Beta from highly corrupted linear measurements y X Beta e w where e is a sparse ...

A so-called extended Lasso optimization is proposed which takes into consideration sparse prior information of both the Lasso and Gaussian design matrix ...

Our first result shows that the extended Lasso can faithfully recover both the regression as well as the corruption vector. Our analysis relies on the notion of ...

Robust Lasso With Missing and Grossly Corrupted Observations. Article. Apr 2013. Nam H. Nguyen · Trac D. Tran. This paper studies the problem of accurately ...

Abstract. We consider the problem of multivariate linear regression with a small fraction of the re- sponses being missing and grossly corrupted, ...