Reversible Jump MCMC Simulated Annealing for Neural Networks

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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Dades bibliogràfiques
Autors principals:	Andrieu, C, de Freitas, N, Doucet, A
Format:	Conference item
Publicat:	Morgan Kaufmann 2000

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