Simulated Stochastic Approximation Annealing for Global Optimization With a Square-Root Cooling Schedule
From MaRDI portal
Publication:4975420
DOI10.1080/01621459.2013.872993zbMath1367.62244OpenAlexW2116626386MaRDI QIDQ4975420
Faming Liang, Guang Lin, Yichen Cheng
Publication date: 4 August 2017
Published in: Journal of the American Statistical Association (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/01621459.2013.872993
stochastic optimizationMarkov chain Monte Carlosimulated annealingstochastic approximation Monte Carlolocal trap
Computational methods in Markov chains (60J22) Monte Carlo methods (65C05) Stochastic approximation (62L20)
Related Items (5)
Computing the halfspace depth with multiple try algorithm and simulated annealing algorithm ⋮ A flexible sequential Monte Carlo algorithm for parametric constrained regression ⋮ Parallel and interacting stochastic approximation annealing algorithms for global optimisation ⋮ Multiple-try simulated annealing algorithm for global optimization ⋮ Support-vector regression accelerated well location optimization: algorithm, validation, and field testing
Cites Work
- Optimization by Simulated Annealing
- 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
- Asymptotic convergence of a simulated annealing algorithm for multiobjective optimization problems
- Asymptotics of the spectral gap with applications to the theory of simulated annealing
- On the use of stochastic approximation Monte Carlo for Monte Carlo integration
- Parametric inference for imperfectly observed Gibbsian fields
- Testing the restrictions implied by the rational expectations hypothesis
- Global optimization by controlled random search
- Global optimization and simulated annealing
- General hit-and-run Monte Carlo sampling for evaluating multidimensional integrals
- Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces
- Stochastic approximation and its applications
- Annealing stochastic approximation Monte Carlo algorithm for neural network training
- General Irreducible Markov Chains and Non-Negative Operators
- Efficient Monte Carlo Procedures for Generating Points Uniformly Distributed over Bounded Regions
- Markov Chains and Stochastic Stability
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
- Geometric convergence and central limit theorems for multidimensional Hastings and Metropolis algorithms
- A stochastic approximation algorithm with Markov chain Monte-Carlo method for incomplete data estimation problems
- Simulated annealing process in general state space
- Dynamic weighting in Monte Carlo and optimization
- Modified controlled random search algorithms
- Stochastic Approximation in Monte Carlo Computation
- Stability of Stochastic Approximation under Verifiable Conditions
- A new approach to variable metric algorithms
- The Convergence of a Class of Double-rank Minimization Algorithms 1. General Considerations
- A Stochastic Approximation Method
- Approximation by superpositions of a sigmoidal function
- An adaptive Metropolis algorithm
This page was built for publication: Simulated Stochastic Approximation Annealing for Global Optimization With a Square-Root Cooling Schedule
