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» Stable Principal Component Pursuit
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CORR
2010
Springer
130views Education» more  CORR 2010»
13 years 3 months ago
Stable Principal Component Pursuit
In this paper, we study the problem of recovering a low-rank matrix (the principal components) from a highdimensional data matrix despite both small entry-wise noise and gross spar...
Zihan Zhou, Xiaodong Li, John Wright, Emmanuel J. ...
CORR
2010
Springer
124views Education» more  CORR 2010»
13 years 3 months ago
Dense Error Correction for Low-Rank Matrices via Principal Component Pursuit
Abstract--We consider the problem of recovering a lowrank matrix when some of its entries, whose locations are not known a priori, are corrupted by errors of arbitrarily large magn...
Arvind Ganesh, John Wright, Xiaodong Li, Emmanuel ...
CORR
2010
Springer
208views Education» more  CORR 2010»
13 years 10 days ago
Real-time Robust Principal Components' Pursuit
In the recent work of Candes et al, the problem of recovering low rank matrix corrupted by i.i.d. sparse outliers is studied and a very elegant solution, principal component pursui...
Chenlu Qiu, Namrata Vaswani
CIKM
2010
Springer
13 years 2 months ago
Decomposing background topics from keywords by principal component pursuit
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...
Kerui Min, Zhengdong Zhang, John Wright, Yi Ma
CORR
2012
Springer
225views Education» more  CORR 2012»
11 years 11 months ago
Compressive Principal Component Pursuit
We consider the problem of recovering a target matrix that is a superposition of low-rank and sparse components, from a small set of linear measurements. This problem arises in co...
John Wright, Arvind Ganesh, Kerui Min, Yi Ma