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» Maximal Discrepancy for Support Vector Machines
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ICPR
2006
IEEE
14 years 8 months ago
Car/Non-Car Classification in an Informative Sample Subspace
In this paper, we present a method for data classification with application to car/non-car objects. We first developed a sample based car/non-car maximal mutual information low di...
Guoping Qiu, Jianzhong Fang
SDM
2009
SIAM
119views Data Mining» more  SDM 2009»
14 years 4 months ago
Twin Vector Machines for Online Learning on a Budget.
This paper proposes Twin Vector Machine (TVM), a constant space and sublinear time Support Vector Machine (SVM) algorithm for online learning. TVM achieves its favorable scaling b...
Zhuang Wang, Slobodan Vucetic
ICML
2009
IEEE
14 years 2 months ago
Fast evolutionary maximum margin clustering
The maximum margin clustering approach is a recently proposed extension of the concept of support vector machines to the clustering problem. Briefly stated, it aims at finding a...
Fabian Gieseke, Tapio Pahikkala, Oliver Kramer
ICONIP
2004
13 years 8 months ago
Morozov, Ivanov and Tikhonov Regularization Based LS-SVMs
This paper contrasts three related regularization schemes for kernel machines using a least squares criterion, namely Tikhonov and Ivanov regularization and Morozov's discrepa...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...
PKDD
2010
Springer
160views Data Mining» more  PKDD 2010»
13 years 5 months ago
Entropy and Margin Maximization for Structured Output Learning
Abstract. We consider the problem of training discriminative structured output predictors, such as conditional random fields (CRFs) and structured support vector machines (SSVMs)....
Patrick Pletscher, Cheng Soon Ong, Joachim M. Buhm...