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AAAI
2007
13 years 10 months ago
Online Co-Localization in Indoor Wireless Networks by Dimension Reduction
This paper addresses the problem of recovering the locations of both mobile devices and access points from radio signals that come in a stream manner, a problem which we call onli...
Jeffrey Junfeng Pan, Qiang Yang, Sinno Jialin Pan
ICML
2004
IEEE
14 years 8 months ago
K-means clustering via principal component analysis
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Chris H. Q. Ding, Xiaofeng He
ISPASS
2006
IEEE
14 years 1 months ago
Comparing multinomial and k-means clustering for SimPoint
SimPoint is a technique used to pick what parts of the program’s execution to simulate in order to have a complete picture of execution. SimPoint uses data clustering algorithms...
Greg Hamerly, Erez Perelman, Brad Calder
BIBM
2008
IEEE
101views Bioinformatics» more  BIBM 2008»
14 years 2 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...
DMIN
2006
146views Data Mining» more  DMIN 2006»
13 years 9 months ago
A Comparison of Two Document Clustering Approaches for Clustering Medical Documents
Medical data is often presented as free text in the form of medical reports. Such documents contain important information about patients, disease progression and management, but ar...
Fathi H. Saad, Beatriz de la Iglesia, Duncan G. Be...