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ICDM
2009
IEEE
154views Data Mining» more  ICDM 2009»
10 years 20 days ago
GSML: A Unified Framework for Sparse Metric Learning
There has been significant recent interest in sparse metric learning (SML) in which we simultaneously learn both a good distance metric and a low-dimensional representation. Unfor...
Kaizhu Huang, Yiming Ying, Colin Campbell
ICPR
2010
IEEE
10 years 26 days ago
On-Line Signature Verification Using 1-D Velocity-Based Directional Analysis
In this paper, we propose a novel approach for identity verification based on the directional analysis of velocity-based partitions of an on-line signature. First, interfeature dep...
Muhammad Talal Ibrahim, Matthew J. Kyan, M. Aurang...
PR
2010
163views more  PR 2010»
10 years 1 months ago
Optimal feature selection for support vector machines
Selecting relevant features for Support Vector Machine (SVM) classifiers is important for a variety of reasons such as generalization performance, computational efficiency, and ...
Minh Hoai Nguyen, Fernando De la Torre
IJON
2010
148views more  IJON 2010»
10 years 1 months ago
Modeling radiation-induced lung injury risk with an ensemble of support vector machines
Radiation-induced lung injury, radiation pneumonitis (RP), is a potentially fatal side-effect of thoracic radiation therapy. In this work, using an ensemble of support vector mac...
Todd W. Schiller, Yixin Chen, Issam El-Naqa, Josep...
TNN
2008
182views more  TNN 2008»
10 years 2 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...
JMLR
2006
150views more  JMLR 2006»
10 years 2 months ago
Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization
Support vector machines utilizing the 1-norm, typically set up as linear programs (Mangasarian, 2000; Bradley and Mangasarian, 1998), are formulated here as a completely unconstra...
Olvi L. Mangasarian
JCB
2006
138views more  JCB 2006»
10 years 2 months ago
Recognition and Classification of Histones Using Support Vector Machine
Histones are DNA-binding proteins found in the chromatin of all eukaryotic cells. They are highly conserved and can be grouped into five major classes: H1/H5, H2A, H2B, H3, and H4...
Manoj Bhasin, Ellis L. Reinherz, Pedro A. Reche
UAI
2000
10 years 4 months ago
Variational Relevance Vector Machines
The Support Vector Machine (SVM) of Vapnik [9] has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions...
Christopher M. Bishop, Michael E. Tipping
NIPS
2001
10 years 4 months ago
Kernel Logistic Regression and the Import Vector Machine
The support vector machine (SVM) is known for its good performance in binary classification, but its extension to multi-class classification is still an on-going research issue. I...
Ji Zhu, Trevor Hastie
DAGM
2004
Springer
10 years 6 months ago
Efficient Face Detection by a Cascaded Support Vector Machine Using Haar-Like Features
Abstract. In this paper, we present a novel method for reducing the computational complexity of a Support Vector Machine (SVM) classifier without significant loss of accuracy. We a...
Matthias Rätsch, Sami Romdhani, Thomas Vetter
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