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JMLR
2012
11 years 10 months ago
Deep Boltzmann Machines as Feed-Forward Hierarchies
The deep Boltzmann machine is a powerful model that extracts the hierarchical structure of observed data. While inference is typically slow due to its undirected nature, we argue ...
Grégoire Montavon, Mikio L. Braun, Klaus-Ro...
IDA
2008
Springer
13 years 8 months ago
Symbolic methodology for numeric data mining
Currently statistical and artificial neural network methods dominate in data mining applications. Alternative relational (symbolic) data mining methods have shown their effectivene...
Boris Kovalerchuk, Evgenii Vityaev
EMNLP
2009
13 years 5 months ago
On the Use of Virtual Evidence in Conditional Random Fields
Virtual evidence (VE), first introduced by (Pearl, 1988), provides a convenient way of incorporating prior knowledge into Bayesian networks. This work generalizes the use of VE to...
Xiao Li
EKAW
2004
Springer
13 years 11 months ago
Medical Ontology and Virtual Staff for a Health Network
In the context of a care network, we describe our method for reconstitution of a medical ontology via the translation of a medical database (DB) towards RDF(S) language. Then we sh...
Rose Dieng-Kuntz, David Minier, Frédé...
NN
2000
Springer
170views Neural Networks» more  NN 2000»
13 years 7 months ago
Synthetic brain imaging: grasping, mirror neurons and imitation
The article contributes to the quest to relate global data on brain and behavior (e.g. from PET, Positron Emission Tomography, and fMRI, functional Magnetic Resonance Imaging) to ...
Michael A. Arbib, Aude Billard, Marco Iacoboni, Er...