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AI
2005
Springer
14 years 2 months ago
Comparing Dimension Reduction Techniques for Document Clustering
In this research, a systematic study is conducted of four dimension reduction techniques for the text clustering problem, using five benchmark data sets. Of the four methods -- Ind...
Bin Tang, Michael A. Shepherd, Malcolm I. Heywood,...
BMCBI
2006
202views more  BMCBI 2006»
13 years 8 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...
CORR
2007
Springer
132views Education» more  CORR 2007»
13 years 8 months ago
Fast Algorithm and Implementation of Dissimilarity Self-Organizing Maps
In many real-world applications, data cannot be accurately represented by vectors. In those situations, one possible solution is to rely on dissimilarity measures that enable a se...
Brieuc Conan-Guez, Fabrice Rossi, Aïcha El Go...
BIBM
2008
IEEE
101views Bioinformatics» more  BIBM 2008»
14 years 3 months ago
Comparing and Clustering Flow Cytometry Data
Flow cytometry technique produces large, multidimensional datasets of properties of individual cells that are helpful for biomedical science and clinical research. This paper expl...
Lin Liu, Li Xiong, James J. Lu, Kim M. Gernert, Vi...
ICRA
2005
IEEE
102views Robotics» more  ICRA 2005»
14 years 2 months ago
SLAM using Incremental Probabilistic PCA and Dimensionality Reduction
— The recent progress in robot mapping (or SLAM) algorithms has focused on estimating either point features (such as landmarks) or grid-based representations. Both of these repre...
Emma Brunskill, Nicholas Roy