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NN
2006
Springer
121views Neural Networks» more  NN 2006»
13 years 7 months ago
Mirror neurons and imitation: A computationally guided review
Neurophysiology reveals the properties of individual mirror neurons in the macaque while brain imaging reveals the presence of `mirror systems' (not individual neurons) in th...
Erhan Oztop, Mitsuo Kawato, Michael A. Arbib
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
FLAIRS
2009
13 years 5 months ago
Multiagent Bayesian Forecasting of Time Series with Graphical Models
Time series are found widely in engineering and science. We study multiagent forecasting in time series, drawing from literature on time series, graphical models, and multiagent s...
Yang Xiang, James Smith, Jeff Kroes
TSMC
1998
91views more  TSMC 1998»
13 years 7 months ago
Toward the border between neural and Markovian paradigms
— A new tendency in the design of modern signal processing methods is the creation of hybrid algorithms. This paper gives an overview of different signal processing algorithms si...
Piotr Wilinski, Basel Solaiman, A. Hillion, W. Cza...
BIBE
2007
IEEE
124views Bioinformatics» more  BIBE 2007»
14 years 1 months ago
Finding Cancer-Related Gene Combinations Using a Molecular Evolutionary Algorithm
—High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray ana...
Chan-Hoon Park, Soo-Jin Kim, Sun Kim, Dong-Yeon Ch...