Robust Principal Component Analysis: A Construction Error Minimization Perspective

TL;DR

This paper introduces a new optimization framework for robust PCA that offers theoretical guarantees and efficient algorithms for practical implementation.

Contribution

It presents a novel construction error minimization approach to robust PCA with rigorous theoretical analysis and computationally efficient algorithms.

Findings

The proposed framework guarantees robustness against data corruption.

Algorithms demonstrate computational efficiency in experiments.

Theoretical analysis confirms convergence and robustness properties.

Abstract

In this paper we propose a novel optimization framework to systematically solve robust PCA problem with rigorous theoretical guarantee, based on which we investigate very computationally economic updating algorithms.