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JMLR
2012
13 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...
RSCTC
2000
Springer
147views Fuzzy Logic» more  RSCTC 2000»
15 years 10 months ago
Towards Rough Neural Computing Based on Rough Membership Functions: Theory and Application
This paper introduces a neural network architecture based on rough sets and rough membership functions. The neurons of such networks instantiate approximate reasoning in assessing ...
James F. Peters, Andrzej Skowron, Liting Han, Shee...
ESANN
1998
15 years 8 months ago
A neural approach to a sensor fusion problem
Our problem concerns the joint interpretation of UltraSonic and InfraRed measurements provided by a composite proximity sensor, in order to extract geometrical and morphological f...
Valentina Colla, Mirko Sgarbi, Leonardo Maria Reyn...
ICDAR
2003
IEEE
16 years 4 days ago
A Neural-Evolutionary Approach for Feature and Architecture Selection in Online Handwriting Recognition
An automatic recognition of online handwritten text has been an on-going research problem for nearly four decades. It has been gaining more interest due to the increasing populari...
Brijesh Verma, Moumita Ghosh
ICA
2010
Springer
15 years 5 months ago
Time Series Causality Inference Using Echo State Networks
One potential strength of recurrent neural networks (RNNs) is their – theoretical – ability to find a connection between cause and consequence in time series in an constraint-...
Norbert Michael Mayer, Oliver Obst, Chang Yu-Chen