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» Lossy Reduction for Very High Dimensional Data
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IJON
2010
121views more  IJON 2010»
14 years 6 months ago
Sample-dependent graph construction with application to dimensionality reduction
Graph construction plays a key role on learning algorithms based on graph Laplacian. However, the traditional graph construction approaches of -neighborhood and k-nearest-neighbor...
Bo Yang, Songcan Chen
CIT
2006
Springer
15 years 1 months ago
A new collision resistant hash function based on optimum dimensionality reduction using Walsh-Hadamard transform
Hash functions play the most important role in various cryptologic applications, ranging from data integrity checking to digital signatures. Our goal is to introduce a new hash fu...
Barzan Mozafari, Mohammad Hasan Savoji
ICIP
2010
IEEE
14 years 7 months ago
Image analysis with regularized Laplacian eigenmaps
Many classes of image data span a low dimensional nonlinear space embedded in the natural high dimensional image space. We adopt and generalize a recently proposed dimensionality ...
Frank Tompkins, Patrick J. Wolfe
CVPR
2007
IEEE
15 years 11 months ago
Trace Ratio vs. Ratio Trace for Dimensionality Reduction
A large family of algorithms for dimensionality reduction end with solving a Trace Ratio problem in the form of arg maxW Tr(WT SpW)/Tr(WT SlW)1 , which is generally transformed in...
Huan Wang, Shuicheng Yan, Dong Xu, Xiaoou Tang, Th...
HPDC
2010
IEEE
14 years 10 months ago
Browsing large scale cheminformatics data with dimension reduction
Visualization of large-scale high dimensional data tool is highly valuable for scientific discovery in many fields. We present PubChemBrowse, a customized visualization tool for c...
Jong Youl Choi, Seung-Hee Bae, Judy Qiu, Geoffrey ...