Work

BayesO: A Bayesian optimization framework in Python

Year: 2023

Type: article

Abstract: Bayesian optimization is a sample-efficient method for solving the optimization of a black-box function.In particular, it successfully shows its effectiveness in diverse applications such as hyperparameter optimization, automated machine learning, material design, sequential assembly, and chemical reaction optimization.In this paper we present an easy-to-use Bayesian optimization framework, referred to as BayesO, which is written in Python and licensed under the MIT license.To briefly introduce our software, we describe the functionality of BayesO and various components for software development.

Source: The Journal of Open Source Software

DOI: 10.21105/joss.05320

Authors: Jungtaek Kim, Seungjin Choi

Institution: University of Pittsburgh

Language: English

Topic: Advanced Bandit Algorithms Research

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: diamond

Funder: Pohang University of Science and Technology

OpenAlex ID: W4387459858