Optimal learning with a local parametric belief model

DOI10.1007/s10898-015-0299-yzbMath1332.90205OpenAlexW2065465845MaRDI QIDQ746825

Bolong Cheng, Warren B. Powell, A. A. Jamshidi

Publication date: 20 October 2015

Published in: Journal of Global Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10898-015-0299-y

zbMATH Keywords

stochastic searchranking and selectionoptimal learninglocal parametric model

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26)

Related Items (2)

A unified framework for stochastic optimization ⋮ Optimal Learning with Local Nonlinear Parametric Models over Continuous Designs

Uses Software

• EGO
• BayesDA

Cites Work

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• Optimal learning for sequential sampling with non-parametric beliefs
• One-dimensional global optimization for observations with noise
• An informational approach to the global optimization of expensive-to-evaluate functions
• Efficient global optimization of expensive black-box functions
• Bayesian look ahead one-stage sampling allocations for selection of the best population
• Global optimization of stochastic black-box systems via sequential kriging meta-models
• The Knowledge Gradient Algorithm for a General Class of Online Learning Problems
• The Knowledge-Gradient Policy for Correlated Normal Beliefs
• The Knowledge-Gradient Algorithm for Sequencing Experiments in Drug Discovery
• The Correlated Knowledge Gradient for Simulation Optimization of Continuous Parameters using Gaussian Process Regression
• A Recursive Local Polynomial Approximation Method Using Dirichlet Clouds and Radial Basis Functions
• Widely Convergent Method for Finding Multiple Solutions of Simultaneous Nonlinear Equations
• A Knowledge-Gradient Policy for Sequential Information Collection
• Towards a Black Box Algorithm for Nonlinear Function Approximation over High‐Dimensional Domains
• Weighted Local Regression and Kernel Methods for Nonparametric Curve Fitting
• Optimal stopping and dynamic allocation
• Two algorithms for one-dimensional multimodai minimization
• Introduction to Stochastic Search and Optimization
• The Continuum-Armed Bandit Problem
• A Stochastic Approximation Method

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