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» Statistical Modelling of CSP Solving Algorithms Performance
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NECO
1998
119views more  NECO 1998»
13 years 8 months ago
Density Estimation by Mixture Models with Smoothing Priors
In the statistical approach for self-organizing maps (SOMs), learning is regarded as an estimation algorithm for a Gaussian mixture model with a Gaussian smoothing prior on the ce...
Akio Utsugi
ACCV
2009
Springer
14 years 3 months ago
Levels of Details for Gaussian Mixture Models
Mixtures of Gaussians are a crucial statistical modeling tool at the heart of many challenging applications in computer vision and machine learning. In this paper, we first descri...
Vincent Garcia, Frank Nielsen, Richard Nock
ICIP
2005
IEEE
14 years 2 months ago
Speckle modeling and reduction in synthetic aperture radar imagery
A new mathematical framework for modeling speckled imagery is introduced based on embedding the spatial correlation properties of speckled imagery, obtained from statistical optic...
Ousseini Lankoande, Majeed M. Hayat, Balu Santhana...
JMLR
2010
163views more  JMLR 2010»
13 years 3 months ago
Dense Message Passing for Sparse Principal Component Analysis
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
Kevin Sharp, Magnus Rattray
ICASSP
2011
IEEE
13 years 20 days ago
Sparse coding and dictionary learning based on the MDL principle
The power of sparse signal coding with learned overcomplete dictionaries has been demonstrated in a variety of applications and fields, from signal processing to statistical infe...
Ignacio Ramírez, Guillermo Sapiro