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NIPS
1996
15 years 4 months ago
Radial Basis Function Networks and Complexity Regularization in Function Learning
In this paper we apply the method of complexity regularization to derive estimation bounds for nonlinear function estimation using a single hidden layer radial basis function netwo...
Adam Krzyzak, Tamás Linder
NPL
1998
87views more  NPL 1998»
15 years 3 months ago
Constrained Learning in Neural Networks: Application to Stable Factorization of 2-D Polynomials
Adaptive artificial neural network techniques are introduced and applied to the factorization of 2-D second order polynomials. The proposed neural network is trained using a const...
Stavros J. Perantonis, Nikolaos Ampazis, Stavros V...
CORR
2010
Springer
127views Education» more  CORR 2010»
15 years 1 months ago
Learning Networks of Stochastic Differential Equations
We consider linear models for stochastic dynamics. To any such model can be associated a network (namely a directed graph) describing which degrees of freedom interact under the d...
José Bento, Morteza Ibrahimi, Andrea Montan...
CN
2010
183views more  CN 2010»
15 years 3 months ago
A learning automata based scheduling solution to the dynamic point coverage problem in wireless sensor networks
The dynamic point coverage problem in wireless sensor networks is to detect some moving target points in the area of the network using as little sensor nodes as possible. One way ...
Mehdi Esnaashari, Mohammad Reza Meybodi
130
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ICML
2009
IEEE
16 years 4 months ago
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling such models to full-sized, high-dimensional images re...
Honglak Lee, Roger Grosse, Rajesh Ranganath, Andre...