Sketching Dictionary Based Robust PCA in Large Matrices

Xingguo Li, Jarvis Haupt

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, our goal is to rapidly locating a few outliers and recover a low dimensional space spanned by inliers, with the particular interest when the outliers have known basis. A simple two-step approach is proposed based on a sketching procedure with theoretical guarantees for the performance. We show that exact identification of the outliers and recovery of the subspace can be achieved using sketched samples as few as the rank plus the number of outliers, ignoring logarithmic factors. This results in significant improvement on both sampling and computational efficiency. Comprehensive numerical experiments are provided to show the efficiency of our proposed method.

Original languageEnglish (US)
Title of host publicationConference Record - 53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages702-706
Number of pages5
ISBN (Electronic)9781728143002
DOIs
StatePublished - Nov 2019
Event53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019 - Pacific Grove, United States
Duration: Nov 3 2019Nov 6 2019

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2019-November
ISSN (Print)1058-6393

Conference

Conference53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019
CountryUnited States
CityPacific Grove
Period11/3/1911/6/19

Keywords

  • data sketching
  • dictionary
  • outlier identification
  • robust PCA

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  • Cite this

    Li, X., & Haupt, J. (2019). Sketching Dictionary Based Robust PCA in Large Matrices. In M. B. Matthews (Ed.), Conference Record - 53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019 (pp. 702-706). [9048695] (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2019-November). IEEE Computer Society. https://doi.org/10.1109/IEEECONF44664.2019.9048695