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Entropy Search (ES) and Predictive Entropy Search (PES) are popular and empirically successful Bayesian Optimization techniques.
The genetical theory of natural selection: a complete variorum edition
Fisher, Ronald Aylmer · 1930
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La distribution de la plus grande de n valeurs
Von Mises, Richard · 1936
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The one-sided barrier problem for Gaussian noise
Slepian, David · 1962
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A new method of locating the maximum point of an arbitrary multipeak curve in the presence of noise
Kushner, Harold J · 1964
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On Bayesian methods for seeking the extremum
Moc̆kus, J · 1974
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Bayesian Learning for Neural networks
Neal, R.M · 1996
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Using confidence bounds for exploitation-exploration tradeoffs
Auer, Peter · 2002
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Gaussian processes for machine learning
Rasmussen, Carl Edward and Williams, Christopher KI · 2006
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Automatic gait optimization with Gaussian process regression
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Concentration Inequalities and Model Selection , volume 6
Massart, Pascal · 2007
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Random features for large-scale kernel machines
Rahimi, Ali, Recht, Benjamin, et al · 2007
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A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and hierarchical reinforcement learning
Brochu, Eric, Cora, Vlad M, and De Freitas, Nando · 2009
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Gaussian process optimization in the bandit setting: no regret and experimental design
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Box2D, a 2D physics engine for games
Catto, Erin · 2011
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Additive Gaussian processes
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Contextual Gaussian process bandit optimization
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Entropy search for information-efficient global optimization
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Wang, Ziyu, Zoghi, Masrour, Hutter, Frank, Matheson, David, and De Freitas, Nando · 2013
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An experimental comparison of Bayesian optimization for bipedal locomotion
Calandra, Roberto, Seyfarth, André, Peters, Jan, and Deisenroth, Marc Peter · 2014
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Predictive entropy search for efficient global optimization of black-box functions
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Output-space predictive entropy search for flexible global optimization
Hoffman, Matthew W and Ghahramani, Zoubin · 2015
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High dimensional Bayesian optimisation and bandits via additive models
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Bayesian optimization with exponential convergence
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Global continuous optimization with error bound and fast convergence
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High dimensional Bayesian optimization via restricted projection pursuit models
Li, Chun-Liang, Kandasamy, Kirthevasan, Póczos, Barnabás, and Schneider, Jeff · 2016
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Optimization as estimation with Gaussian processes in bandit settings
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