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» Nonmonotonic Inferences in Neural Networks
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JMLR
2012
11 years 9 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...
NECO
2008
170views more  NECO 2008»
13 years 7 months ago
Representational Power of Restricted Boltzmann Machines and Deep Belief Networks
Deep Belief Networks (DBN) are generative neural network models with many layers of hidden explanatory factors, recently introduced by Hinton et al., along with a greedy layer-wis...
Nicolas Le Roux, Yoshua Bengio
IJCNN
2008
IEEE
14 years 1 months ago
Out-of-body experiences: False climbs in a supine position?
— Out-of-body experiences (OBEs) are illusions, where people experience themselves as being located outside their physical body and often flying or floating at an elevated loca...
Lars Schwabe, Olaf Blanke
ACSW
2004
13 years 8 months ago
A Market-based Rule Learning System
In this paper, a `market trading' technique is integrated with the techniques of rule discovery and refinement for data mining. A classifier system-inspired model, the market...
Qingqing Zhou, Martin K. Purvis
BMCBI
2008
202views more  BMCBI 2008»
13 years 7 months ago
Network motif-based identification of transcription factor-target gene relationships by integrating multi-source biological data
Background: Integrating data from multiple global assays and curated databases is essential to understand the spatiotemporal interactions within cells. Different experiments measu...
Yuji Zhang, Jianhua Xuan, Benildo de los Reyes, Ro...