2012/04/30 · The goal of this paper is to establish deterministic conditions under which exact recovery of the low-rank and sparse components becomes possible.

Insightful tests with synthetic and real network data corroborate the effectiveness of the novel approach in unveiling traffic anomalies across flows and time, ...

Insightful tests with synthetic and real network data corroborate the effectiveness of the novel approach in unveiling traffic anomalies across flows and time, ...

Abstract—Given the noiseless superposition of a low-rank matrix plus the product of a known fat compression matrix times a sparse matrix, the goal of this ...

An alternating-projection-based fast algorithm to solve the nonconvex RMC problem and converges to the ground-truth low-rank matrix with a linear rate even ...

Insightful tests with synthetic and real network data corroborate the effectiveness of the novel approach in unveiling traffic anomalies across flows and time, ...

2012/07/12 · Mateos, and G. B. Giannakis,``Recovery of Low-Rank Plus Compressed. Sparse Matrices with Application to Unveiling Traffic Anomalies," IEEE Trans ...

2012/04/29 · Abstract—Given the noiseless superposition of a low-rank matrix plus the product of a known fat compression matrix times a sparse matrix ...

Recovery of low-rank plus compressed sparse matrices with application to unveiling traffic anomalies. Morteza Mardani, Gonzalo Mateos, Georgios B. Giannakis.

2012/04/30 · Recovery of Low-Rank Plus Compressed Sparse Matrices with Application to Unveiling Traffic Anomalies†. Morteza Mardani, Gonzalo Mateos, and ...