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» Maximum Margin Clustering with Multivariate Loss Function
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CVPR
2009
IEEE
16 years 4 months ago
Unsupervised Maximum Margin Feature Selection with Manifold Regularization
Feature selection plays a fundamental role in many pattern recognition problems. However, most efforts have been focused on the supervised scenario, while unsupervised feature s...
Bin Zhao, James Tin-Yau Kwok, Fei Wang, Changshui ...
SDM
2009
SIAM
152views Data Mining» more  SDM 2009»
15 years 6 months ago
Multiple Kernel Clustering.
Maximum margin clustering (MMC) has recently attracted considerable interests in both the data mining and machine learning communities. It first projects data samples to a kernel...
Bin Zhao, James T. Kwok, Changshui Zhang
TIP
2008
103views more  TIP 2008»
14 years 9 months ago
Change Detection in Multisensor SAR Images Using Bivariate Gamma Distributions
Abstract--This paper studies a family of distributions constructed from multivariate gamma distributions to model the statistical properties of multisensor synthetic aperture radar...
Florent Chatelain, Jean-Yves Tourneret, Jordi Ingl...
DIS
2001
Springer
15 years 1 months ago
Functional Trees
In the context of classification problems, algorithms that generate multivariate trees are able to explore multiple representation languages by using decision tests based on a com...
Joao Gama
CSDA
2006
98views more  CSDA 2006»
14 years 9 months ago
Fast estimation algorithm for likelihood-based analysis of repeated categorical responses
Likelihood-based marginal regression modelling for repeated, or otherwise clustered, categorical responses is computationally demanding. This is because the number of measures nee...
Jukka Jokinen