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Bayesian optimization

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

Related topics

12 relations
Bayesian experimental designDeep learningDerivative-free optimizationGlobal optimization

Broader (2)

Machine learningStochastic optimization

Papers overview

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2019
2019
Estimating Local Function Complexity via Mixture of Gaussian Processes
Real world data often exhibit inhomogeneity, e.g., the noise level, the sampling distribution or the complexity of the target… 
2018
2018
High-variance multivariate time series forecasting using machine learning
There are several tools and models found in machine learning that can be used to forecast a certain time series; however, it is… 
2018
2018
PHOENICS: A universal deep Bayesian optimizer
In this work we introduce PHOENICS, a probabilistic global optimization algorithm combining ideas from Bayesian optimization with… 
2017
2017
Variational Inference over Non-differentiable Cardiac Simulators using Bayesian Optimization
Performing inference over simulators is generally intractable as their runtime means we cannot compute a marginal likelihood. We… 
2014
2014
Optimizing Without Derivatives: What Does the No Free Lunch Theorem Actually Say?
One of the most important stages in many areas of engineering and applied sciences is modeling and the use of optimization… 
2013
2013
Active Tactile Exploration for Grasping
This paper addresses the problem of robotic grasp optimization. Due to uncertainty both on the robot kinematics, motor control… 
Review
2013
Review
2013
Robot Learning : Some Recent Examples
This paper provides a brief overview of three recent contributions to robot learning developed by researchers at the University… 
2011
2011
Opportunity Cost in Bayesian Optimization
A major advantage of Bayesian optimization is that it generally requires fewer function evaluations than optimization methods… 
2007
2007
FIR Filter Design via Linear Complementarity Problem, Messy Genetic Algorithm, and Ising Messy Genetic Algorithm
— In this paper the design of maximally flat linear phase finite impulse response (FIR) filters is considered. The problem is… 
2000
2000
A C++ Implementation of the Bayesian Optimization Algorithm (BOA) with Decision Graphs
The paper explains how to download compile and use the C implementation of the Bayesian optimization algorithm BOA with decision…