Square Root Principal Component Pursuit: Tuning-Free Noisy Robust Matrix
Recovery
Square Root Principal Component Pursuit: Tuning-Free Noisy Robust Matrix
Recovery
We propose a new framework -- Square Root Principal Component Pursuit -- for low-rank matrix recovery from observations corrupted with noise and outliers. Inspired by the square root Lasso, this new formulation does not require prior knowledge of the noise level. We show that a single, universal choice of the …