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» Training of Support Vector Machines with Mahalanobis Kernels
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PAKDD
2005
ACM
111views Data Mining» more  PAKDD 2005»
15 years 2 months ago
Training Support Vector Machines Using Greedy Stagewise Algorithm
Abstract. Hard margin support vector machines (HM-SVMs) have a risk of getting overfitting in the presence of the noise. Soft margin SVMs deal with this
Liefeng Bo, Ling Wang, Licheng Jiao
ICNC
2005
Springer
15 years 3 months ago
Training Data Selection for Support Vector Machines
Abstract. In recent years, support vector machines (SVMs) have become a popular tool for pattern recognition and machine learning. Training a SVM involves solving a constrained qua...
Jigang Wang, Predrag Neskovic, Leon N. Cooper
ICASSP
2007
IEEE
15 years 3 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
99
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ICPR
2010
IEEE
14 years 8 months ago
Incremental Training of Multiclass Support Vector Machines
We present a new method for the incremental training of multiclass Support Vector Machines that provides computational efficiency for training problems in the case where the trai...
Symeon Nikitidis, Nikos Nikolaidis, Ioannis Pitas
ANNPR
2006
Springer
15 years 1 months ago
Fast Training of Linear Programming Support Vector Machines Using Decomposition Techniques
Abstract. Decomposition techniques are used to speed up training support vector machines but for linear programming support vector machines (LP-SVMs) direct implementation of decom...
Yusuke Torii, Shigeo Abe