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...

Disgrifiad llawn

Manylion Llyfryddiaeth
Prif Awduron:	Andrieu, C, de Freitas, N, Doucet, A
Fformat:	Conference item
Cyhoeddwyd:	Morgan Kaufmann 2000

Eitemau Tebyg

Joint Bayesian model selection and estimation of noisy sinusoids via reversible jump MCMC
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New inference strategies for solving Markov Decision Processes using reversible jump MCMC
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Anisotropic Reversible‐Jump McMC Shear‐Velocity Tomography of the Eastern Alpine Crust
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Hierarchical Bayesian Choice of Laplacian ARMA Models Based on Reversible Jump MCMC Computation
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Ensemble analysis of complex network properties—an MCMC approach
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