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ICDM
2009
IEEE
154views Data Mining» more  ICDM 2009»
8 years 9 months 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
8 years 9 months 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»
8 years 9 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»
8 years 9 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»
8 years 11 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»
8 years 11 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»
8 years 11 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
9 years 15 days 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
9 years 16 days 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
9 years 2 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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