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We introduce Bayesian optimization, a technique developed for optimizing time-consuming engineering simulations and for fitting machine learning models on large datasets.
A statistical approach to some basic mine valuation problems on the witwatersrand
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The origins of kriging
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A computational geometric approach to feasible region division inconstrained global optimization
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Learning in embedded systems
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Optimization using surrogate objectives on a helicopter test example
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Regression with input-dependent noise: A gaussian process treatment
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Efficient Global Optimization of Expensive Black-Box Functions
D.R. Jones, M. Schonlau, and W.J. Welch · 1998
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Reinforcement Learning
R.S. Sutton and A.G. Barto · 1998
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Flexibility and Efficiency Enhancements for Constrained Global Design Optimization with Kriging Approximations
M.J. Sasena · 2002
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The Design and Analysis of Computer Experiments
T.J. Santner, B. W. Willians, and W. Notz · 2003
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Bayesian data analysis
A.B. Gelman, J.B. Carlin, H.S. Stern, and D.B. Rubin · 2004
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Sequential kriging optimization using multiple-fidelity evaluations
D. Huang, T.T. Allen, W.I. Notz, and R.A. Miller · 2006
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Global Optimization of Stochastic Black-Box Systems via Sequential Kriging Meta-Models
D. Huang, T.T. Allen, W.I. Notz, and N. Zeng · 2006
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ParEGO: A hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems
J. Knowles · 2006
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Gaussian Processes for Machine Learning
C.E. Rasmussen and C.K.I. Williams · 2006
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Multi-fidelity optimization via surrogate modelling
A.I.J. Forrester, A. Sóbester, and A.J. Keane · 2007
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A Multi-points Criterion for Deterministic Parallel Global Optimization based on Kriging
D. Ginsbourger, R. Le Riche, and L. Carraro · 2007
The impact of uncertainty on shape optimization of idealized bypass graft models in unsteady flow
S. Sankaran and A.L. Marsden · 2010
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Learning with Dynamic Programming
P.I. Frazier · 2011
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Guessing preferences: A new approach to multi-attribute ranking and selection
P.I. Frazier and A.M. Kazachkov · 2011
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Value of information methods for pairwise sampling with correlations
P.I. Frazier, J. Xie, and S.E. Chick · 2011
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Multi-armed Bandit Allocation Indices
J. Gittins, K. Glazebrook, and R. Weber · 2011
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The knowledge gradient algorithm for sequencing experiments in drug discovery
D.M. Negoescu, P.I. Frazier, and W.B. Powell · 2011
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Most likely heteroscedastic Gaussian process regression
K. Kersting, C. Plagemann, P. Pfaff, and W. Burgard · 2007
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Multi-armed bandit problems
A. Mahajan and D. Teneketzis · 2007
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Engineering design via surrogate modelling: a practical guide
A. Forrester, A. Sobester, and A. Keane · 2008
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A Sequential Design for Approximating the Pareto Front using the Expected Pareto Improvement Function
D.C.T. Bautista · 2009
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A tutorial on bayesian optimization of expensive cost functions, with application to active user modeling and hierarchical reinforcement learning
E. Brochu, M. Cora, and N. de Freitas · 2009
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The knowledge gradient policy for correlated normal beliefs
P.I. Frazier, W.B. Powell, and S. Dayanik · 2009
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The correlated knowledge gradient for simulation optimization of continuous parameters using gaussian process regression
W. Scott, P.I. Frazier, and W.B. Powell · 2011
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Sequential design of computer experiments for the estimation of a probability of failure
J. Bect, D. Ginsbourger, L. Li, V. Picheny, and E. Vazquez · 2012
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Tutorial: Optimization via simulation with bayesian statistics and dynamic programming
P.I. Frazier · 2012
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Dicekriging, diceoptim: Two r packages for the analysis of computer experiments by kriging-based metamodelling and optimization
O. Roustant, D. Ginsbourger, and Y. Deville · 2012
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Practical bayesian optimization of machine learning algorithms
J. Snoek, H. Larochelle, and R.P. Adams · 2012
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Bisection search with noisy responses
R. Waeber, P.I. Frazier, and S.G. Henderson · 2013
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Sequential bayes-optimal policies for multiple comparisons with a known standard
J. Xie and P.I. Frazier · 2013
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Parallel global optimization using an improved multi-points expected improvement criterion
S.C. Clark, J. Wang, E. Liu, and P.I. Frazier · 2014
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Bayesian optimization with inequality constraints
J.R. Gardner, M.J. Kusner, Z. Xu, K. Weinberger, and J.P. Cunningham · 2014
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Gaussian Process Regression with Heteroscedastic Residuals and Fast MCMC Methods
C. Wang · 2014
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http://www.gaussianprocess.org/#code, accessed 2015-02-15
C.E. Rasmussen, 2011 · 2015
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