Bayesian Optimization > 수학/통계학

1 introduction

2 gaussian processes

3 modeling with gaussian processes

4 model assessment, selection, and averaging

5 decision theory for optimization

6 utility functions for optimization

7 common bayesian optimization policies

8 computing policies with gaussian processes

9 implementation

10 theoretical analysis 

11 extensions and related settings

12 a brief history of bayesian optimization

a the gaussian distribution

b methods for approximate bayesian inference 

c gradients

d annotated bibliography of applications