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» Limitations of matrix completion via trace norm minimization
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SIGKDD
2010
151views more  SIGKDD 2010»
13 years 5 months ago
Limitations of matrix completion via trace norm minimization
In recent years, compressive sensing attracts intensive attentions in the field of statistics, automatic control, data mining and machine learning. It assumes the sparsity of the ...
Xiaoxiao Shi, Philip S. Yu
CORR
2011
Springer
144views Education» more  CORR 2011»
13 years 2 months ago
Rank Aggregation via Nuclear Norm Minimization
The process of rank aggregation is intimately intertwined with the structure of skew-symmetric matrices. We apply recent advances in the theory and algorithms of matrix completion...
David F. Gleich, Lek-Heng Lim
CORR
2010
Springer
103views Education» more  CORR 2010»
13 years 11 months ago
Robust Matrix Decomposition with Outliers
Suppose a given observation matrix can be decomposed as the sum of a low-rank matrix and a sparse matrix (outliers), and the goal is to recover these individual components from th...
Daniel Hsu, Sham M. Kakade, Tong Zhang
CORR
2010
Springer
189views Education» more  CORR 2010»
13 years 9 months ago
Robust PCA via Outlier Pursuit
Singular Value Decomposition (and Principal Component Analysis) is one of the most widely used techniques for dimensionality reduction: successful and efficiently computable, it ...
Huan Xu, Constantine Caramanis, Sujay Sanghavi