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» Lossy Reduction for Very High Dimensional Data
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IJON
2010
121views more  IJON 2010»
15 years 3 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 9 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
15 years 4 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
16 years 8 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
15 years 7 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 ...