{"title":"大规模高斯过程建模的全局-局部近似框架","authors":"Akhil Vakayil, V. Roshan Joseph","doi":"10.1080/00401706.2023.2296451","DOIUrl":null,"url":null,"abstract":"In this work, we propose a novel framework for large-scale Gaussian process (GP) modeling. Contrary to the global, and local approximations proposed in the literature to address the computational b...","PeriodicalId":22208,"journal":{"name":"Technometrics","volume":"33 1","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Global-Local Approximation Framework for Large-Scale Gaussian Process Modeling\",\"authors\":\"Akhil Vakayil, V. Roshan Joseph\",\"doi\":\"10.1080/00401706.2023.2296451\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, we propose a novel framework for large-scale Gaussian process (GP) modeling. Contrary to the global, and local approximations proposed in the literature to address the computational b...\",\"PeriodicalId\":22208,\"journal\":{\"name\":\"Technometrics\",\"volume\":\"33 1\",\"pages\":\"\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2023-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Technometrics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1080/00401706.2023.2296451\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technometrics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/00401706.2023.2296451","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
A Global-Local Approximation Framework for Large-Scale Gaussian Process Modeling
In this work, we propose a novel framework for large-scale Gaussian process (GP) modeling. Contrary to the global, and local approximations proposed in the literature to address the computational b...
期刊介绍：
Technometrics is a Journal of Statistics for the Physical, Chemical, and Engineering Sciences, and is published Quarterly by the American Society for Quality and the American Statistical Association.Since its inception in 1959, the mission of Technometrics has been to contribute to the development and use of statistical methods in the physical, chemical, and engineering sciences.
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