Reversible Jump MCMC Simulated Annealing for Neural Networks
We propose a novel reversible jump Markov chain Monte Carlo (MCMC) simulated annealing algorithm to optimize radial basis function (RBF) networks. This algorithm enables us to maximize the joint posterior distribution of the network parameters and the number of basis functions. It performs a global...
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| Format: | Conference item |
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Morgan Kaufmann
2000
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