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» High-dimensional labeled data analysis with Gabriel graphs
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BMCBI
2006
202views more  BMCBI 2006»
13 years 7 months ago
Spectral embedding finds meaningful (relevant) structure in image and microarray data
Background: Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing ...
Brandon W. Higgs, Jennifer W. Weller, Jeffrey L. S...
ICDM
2007
IEEE
149views Data Mining» more  ICDM 2007»
14 years 1 months ago
Temporal Analysis of Semantic Graphs Using ASALSAN
ASALSAN is a new algorithm for computing three-way DEDICOM, which is a linear algebra model for analyzing intrinsically asymmetric relationships, such as trade among nations or th...
Brett W. Bader, Richard A. Harshman, Tamara G. Kol...
ML
2010
ACM
185views Machine Learning» more  ML 2010»
13 years 2 months ago
Learning to rank on graphs
Graph representations of data are increasingly common. Such representations arise in a variety of applications, including computational biology, social network analysis, web applic...
Shivani Agarwal
BMCBI
2008
157views more  BMCBI 2008»
13 years 7 months ago
Dimension reduction with redundant gene elimination for tumor classification
Background: Analysis of gene expression data for tumor classification is an important application of bioinformatics methods. But it is hard to analyse gene expression data from DN...
Xue-Qiang Zeng, Guo-Zheng Li, Jack Y. Yang, Mary Q...
NIPS
2001
13 years 8 months ago
Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering
Drawing on the correspondence between the graph Laplacian, the Laplace-Beltrami operator on a manifold, and the connections to the heat equation, we propose a geometrically motiva...
Mikhail Belkin, Partha Niyogi