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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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2020
2020
Maneuver Optimization for Synthetic Aperture based DOA estimation of GNSS Jammers
GNSS denial via jamming is a low skilled attack which can be performed by nearly anyone using tools which are readily available… 
2017
2017
Cross-genre Document Retrieval: Matching between Conversational and Formal Writings
This paper challenges a cross-genre document retrieval task, where the queries are in formal writing and the target documents are… 
2017
2017
Black-box optimization of 3D integrated systems using machine learning
Increasing complexity of electronics originates new challenges to system optimization. This work proposes a new black box… 
2016
2016
Tomography SAR Imaging Strategy Based on Block-Sparse Model
The compressed sensing (CS) based imaging methods for tomography SAR perform well in the case of large number of baselines… 
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… 
2010
2010
Optimal decoding and minimal length for the non-unique oligonucleotide probe selection problem
2001
2001
THE DISTRIBUTED BAYESIAN OPTIMIZATION ALGORITHM FOR COMBINATORIAL OPTIMIZATION
The Bayesian Optimization Algorithm (BOA) belongs to the probabilistic model building genetic algorithms where crossover and… 
2000
2000
Chapter 17 - Multiscale Statistical Process Control and Model-Based Denoising
1985
1985
Application of Maximum Entropy and Bayesian Optimization Methods to Image Reconstruction from Projections
The problem of image reconstruction from projections is translated, via approximation of the image by linear combination of basis… 
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