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...

Полное описание

Библиографические подробности
Главные авторы:	Andrieu, C, de Freitas, N, Doucet, A
Формат:	Conference item
Опубликовано:	Morgan Kaufmann 2000

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