Adaptive evolutionary Monte Carlo algorithm for optimization with applications to sensor placement problems

No abstract is available for this paper.

• Publication year

  2008

• Venue

  Statistics and computing

• Publication date

  2008-12-01

• Fields of study

  Computer Science, Engineering

• Identifiers
  DOI 10.1007/s11222-008-9079-6
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Coupling and Ergodicity of Adaptive Markov Chain Monte Carlo Algorithms

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• Feature-based classifiers for design optimization

  2007cited by this paper
• Stochastic Approximation in Monte Carlo Computation

  2007cited by this paper
• A review on design, modeling and applications of computer experiments

  2006influential reference
• A survey of inspection strategy and sensor distribution studies in discrete-part manufacturing processes

  2006cited by this paper
• Design and Modeling for Computer Experiments by K.-T. Fang, R. Li and A. Sudjianto

  2006cited by this paper
• Optimization and analysis aid via data-mining for simulated production systems

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• A Generalized Wang–Landau Algorithm for Monte Carlo Computation

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• A Wavelet-based, Distortion Energy Approach to Structural Health Monitoring

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• Optimal coordinate sensor placements for estimating mean and variance components of variation sources

  2005influential reference
• On adaptive Markov chain Monte Carlo algorithms

  2005cited by this paper
• Optimal Engineering System Design Guided by Data-Mining Methods

  2005influential reference
• Design and Modeling for Computer Experiments (Computer Science & Data Analysis)

  2005cited by this paper
• Identification of Regeneration Times in MCMC Simulation, With Application to Adaptive Schemes

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• Design and Modeling for Computer Experiments

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• Techniques for efficient road-network-based tracking of moving objects

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• LEARNABLE EVOLUTION MODEL: Evolutionary Processes Guided by Machine Learning

  2004cited by this paper
• General state space Markov chains and MCMC algorithms

  2004cited by this paper
• Efficient simulation-based discrete optimization

  2004cited by this paper
• The Elements of Statistical Learning

  2003cited by this paper
• Distributed target classification and tracking in sensor networks

  2003cited by this paper
• Characterization of general systematic form errors for circular features

  2003cited by this paper
• Applied Multivariate Statistical Analysis

  2003cited by this paper
• A new algorithm for evaluating form error: the valid characteristic point method with the rapidly contracted constraint zone

  2003cited by this paper
• Panel session: opportunities for simulation in supply chain management

  2002cited by this paper
• Controlled MCMC for Optimal Sampling

  2001cited by this paper
• Data Mining for Design and Manufacturing

  2001cited by this paper
• Roundness modeling of machined parts for tolerance analysis

  2001cited by this paper
• An adaptive Metropolis algorithm

  2001cited by this paper
• Real-Parameter Evolutionary Monte Carlo With Applications to Bayesian Mixture Models

  2001influential reference
• Evolutionary Monte Carlo: Applications to C_p Model Sampling and Change Point Problem

  2000influential reference
• EVOLUTIONARY MONTE CARLO: APPLICATIONS TO Cp MODEL SAMPLING AND CHANGE POINT PROBLEM

  2000influential reference
• A study on analyzing the problem of the spherical form error

  2000cited by this paper
• An exact minimum zone solution for sphericity evaluation

  1999cited by this paper
• Bayesian spatial prediction

  1999cited by this paper
• State Space Modeling of Sheet Metal Assembly for Dimensional Control

  1999cited by this paper
• Analysis of minimum zone sphericity error using minimum potential energy theory

  1999cited by this paper
• An exact solution for the roundness evaluation problems

  1999cited by this paper
• Learning to set up numerical optimizations of engineering designs

  1998cited by this paper
• Adaptive Markov Chain Monte Carlo through Regeneration

  1998cited by this paper
• Design and analysis of computer experiments

  1998cited by this paper
• Markov Chain Monte Carlo in Practice

  1997cited by this paper
• Dynamic weighting in Monte Carlo and optimization.

  1997cited by this paper
• On the Use of Statistics in Design and the Implications for Deterministic Computer Experiments

  1997cited by this paper
• Geometric convergence and central limit theorems for multidimensional Hastings and Metropolis algorithms

  1996cited by this paper
• Asymptotics for REML estimation of spatial covariance parameters

  1996cited by this paper
• Rates of convergence of the Hastings and Metropolis algorithms

  1996influential reference
• Dimensional Measurement Data Analysis: Part II — Minimum Zone Evaluation

  1996cited by this paper
• A Multivariate Statistical Approach to Metrology

  1996cited by this paper
• Bayesian learning for neural networks

  1995cited by this paper
• Introducing Markov chain Monte Carlo

  1995cited by this paper
• Minorization Conditions and Convergence Rates for Markov Chain Monte Carlo

  1995cited by this paper
• Computing Gaussian Likelihoods and Their Derivatives for General Linear Mixed Models

  1994cited by this paper
• Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, by John H. Holland MIT Press (Bradford Books), Cambridge, Mass., 1992, xiv+211 pp. (Paperback £13.50, cloth £26.95)

  1993cited by this paper
• Criteria for Computer-Aided Form Evaluation

  1991cited by this paper
• New approach for evaluating form errors of engineering surfaces

  1987cited by this paper
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images

  1984cited by this paper
• Generalized descent for global optimization

  1981cited by this paper
• On the Experimental Attainment of Optimum Conditions

  1951influential reference

• A Review of Smart Camera Sensor Placement in Construction

  2024cites this paper
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  2023cites this paper
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  2019cites this paper
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  2018cites this paper
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  2018cites this paper
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• Multidimensional Analysis of Non-Standard Neutrino Interactions Using the Proposed ESS$\nu$SB Experiment

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• Serial identification of EEG patterns using adaptive wavelet-based analysis

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• Adaptive wavelet analysis of optical coherent tomography data: Application in problems of diagnostics

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• Abrupt Motion Tracking Via Intensively Adaptive Markov-Chain Monte Carlo Sampling

  2012cites this paper
• Optimización de Monte Carlo usando la distribución beta

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• Abrupt motion tracking via adaptive stochastic approximation Monte Carlo sampling

  2010cites this paper
• Exploring the common concepts of adaptive MCMC and Covariance Matrix Adaptation schemes

  2010cites this paper
• Inference and experimental design for percolation and random graph models.

  2010cites this paper
• Editorial: Special issue on adaptive Monte Carlo methods

  2008cites this paper