gp-optimization-matlab

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gp-optimization-matlab

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MATLAB implementation of my Bayesian Optimization algorithms

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# Gp Optimization

The MATLAB code provided here includes several optimization algorithms (purely sequential or batch) using Gaussian processes. Available algorithms include GP-UCB, EI, Chaining-UCB for sequential optimization, and GP-UCB-PE, GP-B-UCB for batch optimization. The implementation uses efficient updating formulae in order to remain scalable to a large number of training points.

## Documentation

Please go to http://econtal.perso.math.cnrs.fr/software/ for example of use and documentation.

## Relevant publications

**Statistical Learning Approaches for Global Optimization**  
Emile Contal  
PhD  
http://econtal.perso.math.cnrs.fr/publications/phd.pdf

**Stochastic Process Bandits: Upper Confidence Bounds Algorithms via Generic Chaining**  
Emile Contal, Nicolas Vayatis  
http://arxiv.org/pdf/1602.04976v1.pdf

**A Ranking Approach to Global Optimization**  
Cédric Malherbe, Emile Contal, Nicolas Vayatis  
ICML 2016  
http://arxiv.org/pdf/1603.04381v1.pdf

**Optimization for Gaussian Processes via Chaining**  
Emile Contal, Cédric Malherbe, Nicolas Vayatis  
NIPS Workshop on Bayesian Optimization  
http://arxiv.org/pdf/1510.05576v1.pdf

**Gaussian Process Optimization with Mutual Information**  
Emile Contal, Vianney Perchet, Nicolas Vayatis  
ICML 2014  
http://jmlr.csail.mit.edu/proceedings/papers/v32/contal14.pdf

**Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Exploration**  
ECML 2013  
Emile Contal, David Buffoni, Alexandre Robicquet, Nicolas Vayatis  
http://arxiv.org/pdf/1304.5350v3.pdf

gp-optimization-matlab

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