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Bayesian optimization

Bayesian optimization is a sequential design strategyfor global optimization of black-box functions that doesn't require derivatives.
Wikipedia

Papers overview

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Review
2018
Review
2018
Bayesian optimization is an approach to optimizing objective functions that take a long time (minutes or hours) to evaluate. It… 
Review
2016
Review
2016
Big Data applications are typically associated with systems involving large numbers of users, massive complex software systems… 
Highly Cited
2016
Highly Cited
2016
Bayesian optimization is a prominent method for optimizing expensive-to-evaluate black-box functions that is widely applied to… 
Highly Cited
2015
Highly Cited
2015
Bayesian optimization is an effective methodology for the global optimization of functions with expensive evaluations. It relies… 
Highly Cited
2014
Highly Cited
2014
Recent work on Bayesian optimization has shown its effectiveness in global optimization of difficult black-box objective… 
Highly Cited
2013
Highly Cited
2013
Bayesian optimization has recently been proposed as a framework for automatically tuning the hyperparameters of machine learning… 
Highly Cited
2012
Highly Cited
2012
The use of machine learning algorithms frequently involves careful tuning of learning parameters and model hyperparameters… 
Review
2010
Review
2010
We present a tutorial on Bayesian optimization, a method of finding the maximum of expensive cost functions. Bayesian… 
Highly Cited
2008
Highly Cited
2008
Global optimization of non-convex functions over real vector spaces is a problem of widespread theoretical and practical interest… 
Highly Cited
1999
Highly Cited
1999
In this paper, an algorithm based on the concepts of genetic algorithms that uses an estimation of a probability distribution of…