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» Learning a Continuous Hidden Variable Model for Binary Data
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ECML
2001
Springer
14 years 1 days ago
Learning of Variability for Invariant Statistical Pattern Recognition
In many applications, modelling techniques are necessary which take into account the inherent variability of given data. In this paper, we present an approach to model class speciï...
Daniel Keysers, Wolfgang Macherey, Jörg Dahme...
JMLR
2010
169views more  JMLR 2010»
13 years 2 months ago
Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images
Deep belief nets have been successful in modeling handwritten characters, but it has proved more difficult to apply them to real images. The problem lies in the restricted Boltzma...
Marc'Aurelio Ranzato, Alex Krizhevsky, Geoffrey E....
SCVMA
2004
Springer
14 years 27 days ago
2D Motion Description and Contextual Motion Analysis: Issues and New Models
Abstract. In this paper, several important issues related to visual motion analysis are addressed with a focus on the type of motion information to be estimated and the way context...
Patrick Bouthemy
EC
2010
176views ECommerce» more  EC 2010»
13 years 4 months ago
Learning Factorizations in Estimation of Distribution Algorithms Using Affinity Propagation
Estimation of distribution algorithms (EDAs) that use marginal product model factorizations have been widely applied to a broad range of, mainly binary, optimization problems. In ...
Roberto Santana, Pedro Larrañaga, Jos&eacut...
IDA
2009
Springer
13 years 5 months ago
Estimating Hidden Influences in Metabolic and Gene Regulatory Networks
We address the applicability of blind source separation (BSS) methods for the estimation of hidden influences in biological dynamic systems such as metabolic or gene regulatory net...
Florian Blöchl, Fabian J. Theis