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CORR
2010
Springer
189views Education» more  CORR 2010»
15 years 15 days 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
TOG
2008
178views more  TOG 2008»
15 years 1 months ago
Edge-preserving decompositions for multi-scale tone and detail manipulation
Many recent computational photography techniques decompose an image into a piecewise smooth base layer, containing large scale variations in intensity, and a residual detail layer...
Zeev Farbman, Raanan Fattal, Dani Lischinski, Rich...
GECCO
2005
Springer
186views Optimization» more  GECCO 2005»
15 years 7 months ago
Subproblem optimization by gene correlation with singular value decomposition
Several ways of using singular value decomposition (SVD), a linear algebra technique typically used for information retrieval, to decompose problems into subproblems are investiga...
Jacob G. Martin
SMA
2008
ACM
150views Solid Modeling» more  SMA 2008»
15 years 1 months ago
Surface matching using consistent pants decomposition
Surface matching is fundamental to shape computing and various downstream applications. This paper develops a powerful pants decomposition framework for computing maps between sur...
Xin Li, Xianfeng Gu, Hong Qin
BMCBI
2008
145views more  BMCBI 2008»
15 years 2 months ago
Mapping gene expression quantitative trait loci by singular value decomposition and independent component analysis
Background: The combination of gene expression profiling with linkage analysis has become a powerful paradigm for mapping gene expression quantitative trait loci (eQTL). To date, ...
Shameek Biswas, John D. Storey, Joshua M. Akey