A dictionary based generalization of robust PCA

Sirisha Rambhatla; Xingguo Li; Jarvis Haupt

doi:10.1109/GlobalSIP.2016.7906054

A dictionary based generalization of robust PCA

Sirisha Rambhatla, Xingguo Li, Jarvis Haupt

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Scopus citations

Abstract

We analyze the decomposition of a data matrix, assumed to be a superposition of a low-rank component and a component which is sparse in a known dictionary, using a convex demixing method. We provide a unified analysis, encompassing both undercomplete and overcomplete dictionary cases, and show that the constituent components can be successfully recovered under some relatively mild assumptions up to a certain global sparsity level. Further, we corroborate our theoretical results by presenting empirical evaluations in terms of phase transitions in rank and sparsity for various dictionary sizes.

Original language	English (US)
Title of host publication	2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1315-1319
Number of pages	5
ISBN (Electronic)	9781509045457
DOIs	https://doi.org/10.1109/GlobalSIP.2016.7906054
State	Published - Apr 19 2017
Event	2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Washington, United States Duration: Dec 7 2016 → Dec 9 2016

Publication series

Name	2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings

Other

Other	2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016
Country/Territory	United States
City	Washington
Period	12/7/16 → 12/9/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

Dictionary sparse
Low-rank
Robust PCA

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10.1109/GlobalSIP.2016.7906054

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Rambhatla, S., Li, X., & Haupt, J. (2017). A dictionary based generalization of robust PCA. In 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings (pp. 1315-1319). Article 7906054 (2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobalSIP.2016.7906054

A dictionary based generalization of robust PCA. / Rambhatla, Sirisha; Li, Xingguo; Haupt, Jarvis.
2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1315-1319 7906054 (2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Rambhatla, S, Li, X & Haupt, J 2017, A dictionary based generalization of robust PCA. in 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings., 7906054, 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 1315-1319, 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016, Washington, United States, 12/7/16. https://doi.org/10.1109/GlobalSIP.2016.7906054

Rambhatla S, Li X, Haupt J. A dictionary based generalization of robust PCA. In 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1315-1319. 7906054. (2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings). doi: 10.1109/GlobalSIP.2016.7906054

Rambhatla, Sirisha ; Li, Xingguo ; Haupt, Jarvis. / A dictionary based generalization of robust PCA. 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1315-1319 (2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings).

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A dictionary based generalization of robust PCA

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