GPgym: A Remote Service Platform with Gaussian Process Regression for Online Learning

Fuente: arXiv
Guardado en:
Detalles Bibliográficos
Autores principales: Dai, Xiaobing, Yang, Zewen
Formato: Preprint
Publicado: 2024
Materias:
Acceso en línea:
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
_version_ 1866915069348020224
author Dai, Xiaobing
Yang, Zewen
author_facet Dai, Xiaobing
Yang, Zewen
contents Machine learning is now widely applied across various domains, including industry, engineering, and research. While numerous mature machine learning models have been open-sourced on platforms like GitHub, their deployment often requires writing scripts in specific programming languages, such as Python, C++, or MATLAB. This dependency on particular languages creates a barrier for professionals outside the field of machine learning, making it challenging to integrate these algorithms into their workflows. To address this limitation, we propose GPgym, a remote service node based on Gaussian process regression. GPgym enables experts from diverse fields to seamlessly and flexibly incorporate machine learning techniques into their existing specialized software, without needing to write or manage complex script code.
format Preprint
id arxiv_https___arxiv_org_abs_2412_13276
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle GPgym: A Remote Service Platform with Gaussian Process Regression for Online Learning
Dai, Xiaobing
Yang, Zewen
Machine Learning
Machine learning is now widely applied across various domains, including industry, engineering, and research. While numerous mature machine learning models have been open-sourced on platforms like GitHub, their deployment often requires writing scripts in specific programming languages, such as Python, C++, or MATLAB. This dependency on particular languages creates a barrier for professionals outside the field of machine learning, making it challenging to integrate these algorithms into their workflows. To address this limitation, we propose GPgym, a remote service node based on Gaussian process regression. GPgym enables experts from diverse fields to seamlessly and flexibly incorporate machine learning techniques into their existing specialized software, without needing to write or manage complex script code.
title GPgym: A Remote Service Platform with Gaussian Process Regression for Online Learning
topic Machine Learning
url https://arxiv.org/abs/2412.13276