An overview of stochastic approximation Monte Carlo

Cites Work

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Optimization by Simulated Annealing
A theory for the multiset sampler
Equi-energy sampler with applications in statistical inference and statistical mechanics
Trajectory averaging for stochastic approximation MCMC algorithms
Markov chains and stochastic stability
A numerical evaluation of several stochastic algorithms on selected continuous global optimization test problems
Improving SAMC using smoothing methods: Theory and applications to Bayesian model selection problems
On the ergodicity properties of some adaptive MCMC algorithms
Stochastic approximation Monte Carlo importance sampling for approximating exact conditional probabilities
Bayesian analysis for exponential random graph models using the adaptive exchange sampler
Asymptotics of the spectral gap with applications to the theory of simulated annealing
Learning Bayesian networks for discrete data
On the use of stochastic approximation Monte Carlo for Monte Carlo integration
Testing the restrictions implied by the rational expectations hypothesis
Slice sampling. (With discussions and rejoinder)
Annealing stochastic approximation Monte Carlo algorithm for neural network training
Weak Convergence Rates of Population Versus Single-Chain Stochastic Approximation MCMC Algorithms
A double Metropolis–Hastings sampler for spatial models with intractable normalizing constants
Efficient p-value evaluation for resampling-based tests
Multi-Domain Sampling With Applications to Structural Inference of Bayesian Networks
Advanced Markov Chain Monte Carlo Methods
Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
Geometric convergence and central limit theorems for multidimensional Hastings and Metropolis algorithms
Acceleration of Stochastic Approximation by Averaging
Auxiliary Variable Methods for Markov Chain Monte Carlo with Applications
Dynamic weighting in Monte Carlo and optimization
A Theory for Dynamic Weighting in Monte Carlo Computation
Real-Parameter Evolutionary Monte Carlo With Applications to Bayesian Mixture Models
Dynamically Weighted Importance Sampling in Monte Carlo Computation
The Multiple-Try Method and Local Optimization in Metropolis Sampling
Asymptotic Efficiency of Perturbation-Analysis-Based Stochastic Approximation with Averaging
Bayesian Inference in Econometric Models Using Monte Carlo Integration
Minorization Conditions and Convergence Rates for Markov Chain Monte Carlo
Annealing Markov Chain Monte Carlo with Applications to Ancestral Inference
Exact sampling with coupled Markov chains and applications to statistical mechanics
Longitudinal functional principal component modelling via Stochastic Approximation Monte Carlo
Simulated Stochastic Approximation Annealing for Global Optimization With a Square-Root Cooling Schedule
Equation of State Calculations by Fast Computing Machines
The Multiset Sampler
Stochastic Approximation in Monte Carlo Computation
Stability of Stochastic Approximation under Verifiable Conditions
Bayesian Subset Modeling for High-Dimensional Generalized Linear Models
Abrupt Motion Tracking Via Intensively Adaptive Markov-Chain Monte Carlo Sampling
A Monte Carlo Metropolis-Hastings Algorithm for Sampling from Distributions with Intractable Normalizing Constants
An efficient Markov chain Monte Carlo method for distributions with intractable normalising constants
Monte Carlo sampling methods using Markov chains and their applications
A Generalized Wang–Landau Algorithm for Monte Carlo Computation
A Stochastic Approximation Method
Annealing evolutionary stochastic approximation Monte Carlo for global optimization
An adaptive Metropolis algorithm

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