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arXiv · 1406.1089

A variational approach to stable principal component pursuit

Aleksandr Aravkin·Stephen Becker·Volkan Cevher·Peder Olsen
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Abstract

We introduce a new convex formulation for stable principal component pursuit (SPCP) to decompose noisy signals into low-rank and sparse representations. For numerical solutions of our SPCP formulation, we first develop a convex variational framework and then accelerate it with quasi-Newton methods. We show, via synthetic and real data experiments, that our approach offers advantages over the classical SPCP formulations in scalability and practical parameter selection.

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Aleksandr Aravkin, Stephen Becker, Volkan Cevher, Peder Olsen. 2014-06-04. A variational approach to stable principal component pursuit. https://arxiv.org/abs/1406.1089

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