115 citations · 289 across the 7 of their papers we have counts for
4 papers · 1 filter
Principal Component Pursuit with Reduced Linear Measurements
Arvind Ganesh, Kerui Min, John Wright +1
In this paper, we study the problem of decomposing a superposition of a low-rank matrix and a sparse matrix when a relatively few linear measurements are available. This problem ar…
Compressive Principal Component Pursuit
John Wright, Arvind Ganesh, Kerui Min +1
We consider the problem of recovering a target matrix that is a superposition of low-rank and sparse components, from a small set of linear measurements. This problem arises in com…
Dense Error Correction for Low-Rank Matrices via Principal Component Pursuit
Arvind Ganesh, John Wright, Xiaodong Li +2
We consider the problem of recovering a low-rank matrix when some of its entries, whose locations are not known a priori, are corrupted by errors of arbitrarily large magnitude. It…
Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Matrices
John Wright, Arvind Ganesh, Shankar Rao +1
This paper has been withdrawn due to a critical error near equation (71). This error causes the entire argument of the paper to collapse. Emmanuel Candes of Stanford discovered the…