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» Maximum Margin Clustering with Multivariate Loss Function
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CVPR
2009
IEEE
15 years 20 days 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»
14 years 2 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»
13 years 5 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
13 years 10 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»
13 years 5 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