Robust full Bayesian learning for radial basis networks.

We propose a hierarchical full Bayesian model for radial basis networks. This model treats the model dimension (number of neurons), model parameters, regularization parameters, and noise parameters as unknown random variables. We develop a reversible-jump Markov chain Monte Carlo (MCMC) method to pe...

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Váldodahkkit: Andrieu, C, de Freitas, N, Doucet, A
Materiálatiipa: Journal article
Giella:English
Almmustuhtton: 2001