Provable Dynamic Robust PCA or Robust Subspace Tracking

Understand

Dynamic robust PCA refers to the dynamic (time-varying) extension of robust PCA (RPCA).

• It assumes that the true (uncorrupted) data lies in a low-dimensional subspace that can change with time, albeit slowly.
• The goal is to track this changing subspace over time in the presence of sparse outliers.
• We develop and study a novel algorithm, that we call simple-ReProCS, based on the recently introduced Recursive Projected Compressive Sensing (ReProCS) framework.