Side Information in Robust Principal Component Analysis: Algorithms and Applications
Side Information in Robust Principal Component Analysis: Algorithms and Applications
Robust Principal Component Analysis (RPCA) aims at recovering a low-rank subspace from grossly corrupted high-dimensional (often visual) data and is a cornerstone in many machine learning and computer vision applications. Even though RPCA has been shown to be very successful in solving many rank minimisation problems, there are still cases …