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» Training Data Selection for Support Vector Machines
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80
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ICPR
2004
IEEE
16 years 1 months ago
Learning Sample Subspace with Application to Face Detection
In this paper, we present a novel maximum correlation sample subspace method and apply it to human face detection [1] in still images. The algorithm starts by projecting all the t...
Guoping Qiu, Jianzhong Fang
116
Voted
JMLR
2006
96views more  JMLR 2006»
15 years 12 days 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
125
Voted
BMCBI
2004
252views more  BMCBI 2004»
15 years 9 days ago
Applying Support Vector Machines for Gene ontology based gene function prediction
Background: The current progress in sequencing projects calls for rapid, reliable and accurate function assignments of gene products. A variety of methods has been designed to ann...
Arunachalam Vinayagam, Rainer König, Jutta Mo...
110
Voted
COLING
2002
15 years 8 days ago
Efficient Support Vector Classifiers for Named Entity Recognition
Named Entity (NE) recognition is a task in which proper nouns and numerical information are extracted from documents and are classified into categories such as person, organizatio...
Hideki Isozaki, Hideto Kazawa
ICANN
2007
Springer
15 years 4 months ago
Resilient Approximation of Kernel Classifiers
Abstract. Trained support vector machines (SVMs) have a slow runtime classification speed if the classification problem is noisy and the sample data set is large. Approximating the...
Thorsten Suttorp, Christian Igel