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» Support Vector Regression Using Mahalanobis Kernels
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ICML
2009
IEEE
14 years 9 months ago
Semi-supervised learning using label mean
Semi-Supervised Support Vector Machines (S3VMs) typically directly estimate the label assignments for the unlabeled instances. This is often inefficient even with recent advances ...
Yu-Feng Li, James T. Kwok, Zhi-Hua Zhou
IJIS
2008
123views more  IJIS 2008»
13 years 8 months ago
Algorithms of nonlinear document clustering based on fuzzy multiset model
Abstract: Fuzzy multiset is applicable as a model of information retrieval because it has the mathematical structure which expresses the number and the degree of attribution of an ...
Kiyotaka Mizutani, Ryo Inokuchi, Sadaaki Miyamoto
JMLR
2006
186views more  JMLR 2006»
13 years 8 months ago
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Mikhail Belkin, Partha Niyogi, Vikas Sindhwani
ICMCS
2006
IEEE
208views Multimedia» more  ICMCS 2006»
14 years 2 months ago
An Automatic Classification System Applied in Medical Images
In this paper, a multi-class classification system is developed for medical images. We have mainly explored ways to use different image features, and compared two classifiers: Pri...
Bo Qiu, Chang Xu, Qi Tian
ICONIP
2004
13 years 10 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 ...