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CORR
2010
Springer
189views Education» more  CORR 2010»
14 years 8 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
TOG
2008
178views more  TOG 2008»
14 years 9 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 3 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»
14 years 9 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
98
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BMCBI
2008
145views more  BMCBI 2008»
14 years 9 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