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» The Spectral Method for General Mixture Models
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ICANN
2010
Springer
13 years 8 months ago
Computational Properties of Probabilistic Neural Networks
We discuss the problem of overfitting of probabilistic neural networks in the framework of statistical pattern recognition. The probabilistic approach to neural networks provides a...
Jiri Grim, Jan Hora
BMCBI
2006
202views more  BMCBI 2006»
13 years 7 months ago
Spectral embedding finds meaningful (relevant) structure in image and microarray data
Background: Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing ...
Brandon W. Higgs, Jennifer W. Weller, Jeffrey L. S...
WACV
2008
IEEE
14 years 2 months ago
Background Subtraction for Temporally Irregular Dynamic Textures
In the traditional mixture of Gaussians background model, the generating process of each pixel is modeled as a mixture of Gaussians over color. Unfortunately, this model performs ...
Gerald Dalley, Joshua Migdal, W. Eric L. Grimson
CORR
2007
Springer
99views Education» more  CORR 2007»
13 years 7 months ago
Fast Selection of Spectral Variables with B-Spline Compression
The large number of spectral variables in most data sets encountered in spectral chemometrics often renders the prediction of a dependent variable uneasy. The number of variables ...
Fabrice Rossi, Damien François, Vincent Wer...
ACCV
2010
Springer
13 years 2 months ago
Latent Gaussian Mixture Regression for Human Pose Estimation
Discriminative approaches for human pose estimation model the functional mapping, or conditional distribution, between image features and 3D pose. Learning such multi-modal models ...
Yan Tian, Leonid Sigal, Hernán Badino, Fern...