2024 FFT

The Masked Matrix Separation Problem

Xuemei Chen (UNCW)

Abstract: The problem of separating a known matrix into its low rank and sparse components have found numerous applications in imaging, multimedia processing, statistical modeling, etc. In this talk we will explore this problem in a more complicated setting where the sparse component has been “masked” by a linear transformation. This problem was motivated by an electrodermal activity signal decomposition problem, but we believe it has a wider appeal.