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...

Full beskrivning

Bibliografiska uppgifter
Huvudupphovsmän:	Andrieu, C, de Freitas, N, Doucet, A
Materialtyp:	Conference item
Publicerad:	Morgan Kaufmann 2000

Liknande verk

Joint Bayesian model selection and estimation of noisy sinusoids via reversible jump MCMC
av: Andrieu, C, et al.
Publicerad: (1999)

New inference strategies for solving Markov Decision Processes using reversible jump MCMC
av: Hoffman, M, et al.
Publicerad: (2009)

New inference strategies for solving Markov Decision Processes using reversible jump MCMC
av: Hoffman, M, et al.
Publicerad: (2009)

Sequential MCMC for Bayesian model selection
av: Andrieu, C, et al.
Publicerad: (1999)

An Introduction to MCMC for Machine Learning
av: Andrieu, C, et al.
Publicerad: (2003)

An introduction to MCMC for machine learning
av: Andrieu, C, et al.
Publicerad: (2003)

Reversible Jump MCMC for Deghosting in MSPSR Systems
av: Pavel Kulmon
Publicerad: (2021-07-01)

Model selection by MCMC computation
av: Andrieu, C, et al.
Publicerad: (2001)

Sequential MCMC for Bayesian model selection
av: Andrieu, C, et al.
Publicerad: (1999)

RETRACTED: Implementation of reversible jump MCMC algorithm to segment the piecewise Polynomial Regression
av: Suparman Suparman
Publicerad: (2016-07-01)

Bayesian curve fitting using MCMC with applications to signal segmentation
av: Punskaya, E, et al.
Publicerad: (2002)

Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm
av: Suparman, S., et al.
Publicerad: (2018)

Hierarchical Bayesian Choice of Laplacian ARMA Models Based on Reversible Jump MCMC Computation
av: Suparman
Publicerad: (2020-03-01)

Anisotropic Reversible‐Jump McMC Shear‐Velocity Tomography of the Eastern Alpine Crust
av: E. D. Kästle, et al.
Publicerad: (2024-03-01)

Bayesian Policy Learning with Trans−Dimensional MCMC
av: Hoffman, M, et al.
Publicerad: (2007)

Trans-dimensional MCMC for Bayesian policy learning
av: Hoffman, M, et al.
Publicerad: (2009)

Non-reversible parallel tempering: a scalable highly parallel MCMC scheme
av: Syed, S, et al.
Publicerad: (2021)

Fast MCMC sampling for Markov jump processes and extensions
av: Rao, V, et al.
Publicerad: (2013)

Convergence of simulated annealing using Foster-Lyapunov criteria
av: Andrieu, C, et al.
Publicerad: (2001)

Simulated annealing for maximum A Posteriori parameter estimation of hidden Markov models
av: Andrieu, C, et al.
Publicerad: (2000)

Fast MCMC sampling for Markov jump processes and continuous time Bayesian networks
av: Rao, V, et al.
Publicerad: (2011)

Reversible jump Markov chain Monte Carlo strategies for Bayesian model selection in autoregressive processes
av: Vermaak, J, et al.
Publicerad: (2004)

Limit theorems for sequential MCMC methods
av: Finke, A, et al.
Publicerad: (2020)

Variational MCMC
av: de Freitas, N, et al.
Publicerad: (2001)

Uma abordagem bayesiana para o mapeamento de QTLS utilizando o método MCMC com saltos reversíveis A bayesian approach to map QTLs using reversible jump MCMC
av: Joseane Padilha da Silva, et al.
Publicerad: (2009-08-01)

Bayesian Graph Convolutional Neural Networks via Tempered MCMC
av: Rohitash Chandra, et al.
Publicerad: (2021-01-01)

Iterative algorithms for state estimation of jump Markov linear systems
av: Doucet, A, et al.
Publicerad: (2001)

Adaptive MCMC with Bayesian Optimization
av: Mahendran, N, et al.
Publicerad: (2012)

Robust full Bayesian methods for neural networks
av: Andrieu, C, et al.
Publicerad: (2000)

A Neural Network MCMC Sampler That Maximizes Proposal Entropy
av: Zengyi Li, et al.
Publicerad: (2021-02-01)

EXTRACTING LANE GEOMETRY AND TOPOLOGY INFORMATION FROM VEHICLE FLEET TRAJECTORIES IN COMPLEX URBAN SCENARIOS USING A REVERSIBLE JUMP MCMC METHOD
av: O. Roeth, et al.
Publicerad: (2017-05-01)

Clone MCMC: Parallel high-dimensional Gaussian gibbs sampling
av: Bǎrbos, A, et al.
Publicerad: (2018)

Bayesian Neural Networks via MCMC: A Python-Based Tutorial
av: Rohitash Chandra, et al.
Publicerad: (2024-01-01)

Determining the order of a moving average model of time series using reversible jump MCMC: a comparison between laplacian and gaussian noises
av: Suparman, Suparman, et al.
Publicerad: (2020)

Intracluster Moves for Constrained Discrete−Space MCMC
av: Hamze, F, et al.
Publicerad: (2010)

Simulation and Monte Carlo : with applications in finance and MCMC /
av: 330909 Dagpunar, J. S.
Publicerad: (2007)

Efficient particle filtering for jump Markov systems. Application to time-varying autoregressions
av: Andrieu, C, et al.
Publicerad: (2003)

Efficient MCMC sampling with dimension-free convergence rate using ADMM-type splitting
av: Vono, M, et al.
Publicerad: (2022)

Neural Network Structure Optimization by Simulated Annealing
av: Chun Lin Kuo, et al.
Publicerad: (2022-02-01)

Sparse neural network optimization by Simulated Annealing
av: Ercan Engin Kuruoglu, et al.
Publicerad: (2023-09-01)