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» Modeling spiking neural networks
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IJON
2006
76views more  IJON 2006»
15 years 1 months ago
Evolving networks of integrate-and-fire neurons
This paper addresses the following question: ``What neural circuits can emulate the monosynaptic correlogram generated by a direct connection between two neurons?'' The ...
Francisco J. Veredas, Francisco J. Vico, Jos&eacut...
EUROPAR
2005
Springer
15 years 7 months ago
An Approach to Performance Prediction for Parallel Applications
Abstract. Accurately modeling and predicting performance for largescale applications becomes increasingly difficult as system complexity scales dramatically. Analytic predictive mo...
Engin Ipek, Bronis R. de Supinski, Martin Schulz, ...
137
Voted
JMLR
2010
143views more  JMLR 2010»
14 years 8 months ago
Incremental Sigmoid Belief Networks for Grammar Learning
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
James Henderson, Ivan Titov
IPPS
1998
IEEE
15 years 6 months ago
Multiprocessor Scheduling Using Mean-Field Annealing
This paper presents our work on the static task scheduling model using the mean-field annealing (MFA) technique. Mean-field annealing is a technique of thermostatic annealing that...
Shaharuddin Salleh, Albert Y. Zomaya
135
Voted
IJCNN
2008
IEEE
15 years 8 months ago
Fully complex-valued radial basis function networks for orthogonal least squares regression
— We consider a fully complex-valued radial basis function (RBF) network for regression application. The locally regularised orthogonal least squares (LROLS) algorithm with the D...
Sheng Chen, Xia Hong, Chris J. Harris