Skip to content

Implementation of the Principled Optimistic Preferential Bayesian Optimization (POP-BO) algorithm.

Notifications You must be signed in to change notification settings

PREDICT-EPFL/POP-BO

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 
 
 
 
 

Repository files navigation

POP-BO

Code for the paper "Principled Preferential Bayesian Optimization" arXiv. POP-BO stands for 'Principled Optimistic Preferential Bayesian Optimization'.

Installation

Under this directory, run pip install ..

Getting started

You can run the demo.ipynb under "./popbo/demo"

Requirements

The required Python dependencies include:

The following packages are also required:

We also reused test functions in the repo:

About

Implementation of the Principled Optimistic Preferential Bayesian Optimization (POP-BO) algorithm.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages