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TIP
2010
112views more  TIP 2010»
14 years 8 months ago
Variable Density Compressed Image Sampling
Compressed sensing (CS) provides an efficient way to acquire and reconstruct natural images from a reduced number of linear projection measurements at sub-Nyquist sampling rates....
Zhongmin Wang, Gonzalo R. Arce
GRC
2010
IEEE
14 years 11 months ago
Learning Multiple Latent Variables with Self-Organizing Maps
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
Lili Zhang, Erzsébet Merényi
CISS
2008
IEEE
15 years 4 months ago
Information theory based estimator of the number of sources in a sparse linear mixing model
—In this paper we present an Information Theoretic Estimator for the number of sources mutually disjoint in a linear mixing model. The approach follows the Minimum Description Le...
Radu Balan
IJON
2007
134views more  IJON 2007»
14 years 10 months ago
Analysis of SVM regression bounds for variable ranking
This paper addresses the problem of variable ranking for Support Vector Regression. The relevance criteria that we proposed are based on leave-one-out bounds and some variants and...
Alain Rakotomamonjy
NIPS
1998
14 years 11 months ago
Learning a Continuous Hidden Variable Model for Binary Data
A directed generative model for binary data using a small number of hidden continuous units is investigated. A clipping nonlinearity distinguishes the model from conventional prin...
Daniel D. Lee, Haim Sompolinsky