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ICIC
2005
Springer
14 years 27 days ago
Methods of Decreasing the Number of Support Vectors via k-Mean Clustering
This paper proposes two methods which take advantage of k -mean clustering algorithm to decrease the number of support vectors (SVs) for the training of support vector machine (SVM...
Xiao-Lei Xia, Michael R. Lyu, Tat-Ming Lok, Guang-...
ISBI
2002
IEEE
14 years 8 months ago
Support vector machine learning for detection of microcalcifications in mammograms
Microcalcification (MC) clusters in mammograms can be an indicator of breast cancer. In this work we propose for the first time the use of support vector machine (SVM) learning fo...
Issam El-Naqa, Yongyi Yang, Miles N. Wernick, Niko...
JMLR
2006
96views more  JMLR 2006»
13 years 7 months ago
A Hierarchy of Support Vector Machines for Pattern Detection
We introduce a computational design for pattern detection based on a tree-structured network of support vector machines (SVMs). An SVM is associated with each cell in a recursive ...
Hichem Sahbi, Donald Geman
ICMCS
2005
IEEE
229views Multimedia» more  ICMCS 2005»
14 years 29 days ago
A methodology for improving recognition rate of linear discriminant analysis in video-based face recognition using support vecto
This paper proposes a two-step methodology for improving the discriminatory power of Linear Discriminant Analysis (LDA) for video-based human face recognition. Results indicate th...
Sreekar Krishna, Sethuraman Panchanathan
NIPS
2000
13 years 8 months ago
A Support Vector Method for Clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladi...