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...
Main Authors: | Andrieu, C, de Freitas, N, Doucet, A |
---|---|
פורמט: | Conference item |
יצא לאור: |
Morgan Kaufmann
2000
|
פריטים דומים
-
Joint Bayesian model selection and estimation of noisy sinusoids via reversible jump MCMC
מאת: Andrieu, C, et al.
יצא לאור: (1999) -
New inference strategies for solving Markov Decision Processes using reversible jump MCMC
מאת: Hoffman, M, et al.
יצא לאור: (2009) -
New inference strategies for solving Markov Decision Processes using reversible jump MCMC
מאת: Hoffman, M, et al.
יצא לאור: (2009) -
Sequential MCMC for Bayesian model selection
מאת: Andrieu, C, et al.
יצא לאור: (1999) -
An Introduction to MCMC for Machine Learning
מאת: Andrieu, C, et al.
יצא לאור: (2003)