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» Interval discriminant analysis using support vector machines
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WACV
2002
IEEE
15 years 10 months ago
An Experimental Evaluation of Linear and Kernel-Based Methods for Face Recognition
In this paper we present the results of a comparative study of linear and kernel-based methods for face recognition. The methods used for dimensionality reduction are Principal Co...
Himaanshu Gupta, Amit K. Agrawal, Tarun Pruthi, Ch...
COLT
1999
Springer
15 years 9 months ago
Covering Numbers for Support Vector Machines
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Ro...
BMCBI
2004
114views more  BMCBI 2004»
15 years 5 months ago
Profiled support vector machines for antisense oligonucleotide efficacy prediction
Background: This paper presents the use of Support Vector Machines (SVMs) for prediction and analysis of antisense oligonucleotide (AO) efficacy. The collected database comprises ...
Gustavo Camps-Valls, Alistair M. Chalk, Antonio J....
ICASSP
2007
IEEE
15 years 11 months ago
A Self-Training Semi-Supervised Support Vector Machine Algorithm and its Applications in Brain Computer Interface
In this paper, we analyze the convergence of an iterative selftraining semi-supervised support vector machine (SVM) algorithm, which is designed for classi cation in small trainin...
Yuanqing Li, Huiqi Li, Cuntai Guan, Zhengyang Chin
179
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ICPR
2006
IEEE
15 years 11 months ago
An Improved Semi-Supervised Support Vector Machine Based Translation Algorithm for BCI Systems
In this study, we propose an improved semi-supervised support vector machine (SVM) based translation algorithm for brain-computer interface (BCI) systems, aiming at reducing the t...
Jianzhao Qin, Yuanqing Li