{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T02:11:03Z","timestamp":1778638263452,"version":"3.51.4"},"reference-count":39,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,12,10]],"date-time":"2023-12-10T00:00:00Z","timestamp":1702166400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,12,10]],"date-time":"2023-12-10T00:00:00Z","timestamp":1702166400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100002186","name":"Lockheed Martin","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100002186","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,12,10]]},"DOI":"10.1109\/wsc60868.2023.10408654","type":"proceedings-article","created":{"date-parts":[[2024,1,31]],"date-time":"2024-01-31T18:30:14Z","timestamp":1706725814000},"page":"564-575","source":"Crossref","is-referenced-by-count":1,"title":["CGPT: A Conditional Gaussian Process Tree for Grey-Box Bayesian Optimization"],"prefix":"10.1109","author":[{"given":"Mengrui Mina","family":"Jiang","sequence":"first","affiliation":[{"name":"Arizona State University,School of Computing and Augmented Intelligence,Tempe,USA,85281"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tanmay","family":"Khandait","sequence":"additional","affiliation":[{"name":"Arizona State University,School of Computing and Augmented Intelligence,Tempe,USA,85281"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giulia","family":"Pedrielli","sequence":"additional","affiliation":[{"name":"Arizona State University,School of Computing and Augmented Intelligence,Tempe,USA,85281"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","first-page":"54","article-title":"Gp-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning","volume-title":"International Conference on Machine Learning","author":"Achituve"},{"key":"ref2","first-page":"354","article-title":"Bayesian Optimization of Composite Functions","volume-title":"International Conference on Machine Learning","author":"Astudillo"},{"key":"ref3","first-page":"14463","article-title":"Bayesian Optimization of Function Networks","volume":"34","author":"Astudillo","year":"2021a","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/WSC52266.2021.9715343"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1201\/9781315139470"},{"key":"ref6","article-title":"A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning","author":"Brochu","year":"2010"},{"key":"ref7","first-page":"27","article-title":"Tree-Structured Gaussian Process Approximations","author":"Bui","year":"2014","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.compstruct.2020.112882"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/EMSOFT.2015.7318257"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2023.115937"},{"key":"ref11","article-title":"A Tutorial on Bayesian Optimization","author":"Frazier","year":"2018"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2008.4650959"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015367"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1198\/016214508000000689"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2966228"},{"key":"ref16","article-title":"Pareto-Efficient Acquisition Functions for Cost-Aware Bayesian Optimization","author":"Guinet","year":"2020"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33017858"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106247"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299048"},{"key":"ref20","article-title":"Cost-aware Bayesian Optimization","author":"Lee","year":"2020"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2018.10.063"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/COASE.2019.8843005"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1005896"},{"key":"ref24","first-page":"18","article-title":"An Alternative Infinite Mixture of Gaussian Process Experts","author":"Meeds","year":"2005","journal-title":"Advances in Neural Information Processing Systems"},{"issue":"278","key":"ref25","first-page":"1","article-title":"Jump Gaussian Process Model for Estimating Piecewise Continuous Regression Functions","volume":"23","author":"Park","year":"2022","journal-title":"Journal of Machine Learning Research"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/tase.2023.3297984"},{"key":"ref27","first-page":"14","article-title":"Infinite Mixtures of Gaussian Process Experts","author":"Rasmussen","year":"2001","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-73003-5_196"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/s12247-019-09382-8"},{"key":"ref30","volume-title":"The Design and Analysis of Computer Experiments","author":"Santner","year":"2013"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1080\/00401706.2021.2008505"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2015.2494218"},{"key":"ref33","first-page":"18","article-title":"Fast Gaussian Process Regression Using Kd-Trees","author":"Shen","year":"2005","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref34","first-page":"3158","article-title":"A General Framework for Multi-Fidelity Bayesian Optimization with Gaussian Processes","volume-title":"The 22nd International Conference on Artificial Intelligence and Statistics","author":"Song"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2008.IV.040"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TVLSI.2017.2784783"},{"key":"ref37","article-title":"Fast Maritime Anomaly Detection Using Kd-Tree Gaussian Processes","volume-title":"IMA Maths in Defence Conference","author":"Will"},{"key":"ref38","article-title":"Exploiting Gradients and Hessians in Bayesian Optimization and Bayesian Quadrature","author":"Wu","year":"2017"},{"key":"ref39","article-title":"Information-Based Multi-Fidelity Bayesian Optimization","volume-title":"NIPS Workshop on Bayesian Optimization","volume":"49","author":"Zhang"}],"event":{"name":"2023 Winter Simulation Conference (WSC)","location":"San Antonio, TX, USA","start":{"date-parts":[[2023,12,10]]},"end":{"date-parts":[[2023,12,13]]}},"container-title":["2023 Winter Simulation Conference (WSC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10406299\/10407113\/10408654.pdf?arnumber=10408654","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,2]],"date-time":"2024-02-02T00:24:41Z","timestamp":1706833481000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10408654\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,10]]},"references-count":39,"URL":"https:\/\/doi.org\/10.1109\/wsc60868.2023.10408654","relation":{},"subject":[],"published":{"date-parts":[[2023,12,10]]}}}