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ICML
2007
IEEE
16 years 1 months ago
Trust region Newton methods for large-scale logistic regression
Large-scale logistic regression arises in many applications such as document classification and natural language processing. In this paper, we apply a trust region Newton method t...
Chih-Jen Lin, Ruby C. Weng, S. Sathiya Keerthi
INTERSPEECH
2010
14 years 8 months ago
Semi-supervised training of Gaussian mixture models by conditional entropy minimization
In this paper, we propose a new semi-supervised training method for Gaussian Mixture Models. We add a conditional entropy minimizer to the maximum mutual information criteria, whi...
Jui-Ting Huang, Mark Hasegawa-Johnson
BMCBI
2007
178views more  BMCBI 2007»
15 years 1 months ago
SVM clustering
Background: Support Vector Machines (SVMs) provide a powerful method for classification (supervised learning). Use of SVMs for clustering (unsupervised learning) is now being cons...
Stephen Winters-Hilt, Sam Merat
ECCV
2008
Springer
16 years 3 months ago
The Bi-directional Framework for Unifying Parametric Image Alignment Approaches
In this paper, a generic bi-directional framework is proposed for parametric image alignment, that extends the classification of [1]. Four main categories (Forward, Inverse, Depend...
Jean-Baptiste Authesserre, Rémi Mégr...
NA
2006
75views more  NA 2006»
15 years 1 months ago
Least-squares spectral collocation with the overlapping Schwarz method for the incompressible Navier-Stokes equations
A least-squares spectral collocation scheme is combined with the overlapping Schwarz method. The methods are succesfully applied to the incompressible Navier-Stokes equations. The...
Wilhelm Heinrichs