{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T21:18:52Z","timestamp":1773263932461,"version":"3.50.1"},"reference-count":49,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T00:00:00Z","timestamp":1762905600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T00:00:00Z","timestamp":1762905600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,11,12]]},"DOI":"10.1109\/icdmw69685.2025.00200","type":"proceedings-article","created":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T19:50:39Z","timestamp":1773172239000},"page":"1666-1675","source":"Crossref","is-referenced-by-count":0,"title":["A Reproducible Approach to Virtual Metrology"],"prefix":"10.1109","author":[{"given":"Jimmy","family":"P\u00f6hlmann","sequence":"first","affiliation":[{"name":"TUD Dresden University of Technology,Dresden Database Research Group"}]},{"given":"Anna","family":"Lopatkina","sequence":"additional","affiliation":[{"name":"TUD Dresden University of Technology,Dresden Database Research Group"}]},{"given":"Paul","family":"Jungmann","sequence":"additional","affiliation":[{"name":"GlobalFoundries Dresden Module One LLC & Company KG"}]},{"given":"Claudio","family":"Hartmann","sequence":"additional","affiliation":[{"name":"TUD Dresden University of Technology,Dresden Database Research Group"}]},{"given":"Wolfgang","family":"Lehner","sequence":"additional","affiliation":[{"name":"TUD Dresden University of Technology,Dresden Database Research Group"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TSM.2007.901851"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1117\/12.2614943"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1038\/nature13570"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1080\/00207543.2021.1976433"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1117\/12.2259910"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ISSM.2005.1513322"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2006.247284"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/783\/1\/012042"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-04083-2_2"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICSC47195.2019.8950664"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1117\/12.2613202"},{"key":"ref12","article-title":"CRISP-DM: Towards a standard process model for data mining","volume-title":"Proceedings of the 4th International Conference on the Practical Applications of Knowledge Discovery and Data Mining. Manchester","author":"Wirth"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.7717\/peerj-cs.623"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.5757\/asct.2023.32.5.106"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.measen.2021.100046"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1037\/h0042519"},{"key":"ref17","article-title":"LightGBM: A highly efficient gradient boosting decision tree","volume-title":"Proceedings of the 31st International Conference on Neural Information Processing Systems, ser. NIPS\u201917. Curran Associates Inc.","author":"Ke"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.isatra.2020.03.031"},{"key":"ref19","article-title":"Sequential Model-Based Optimization for General Algorithm Configuration (extended version)","volume-title":"Learning and Intelligent Optimization - 5th International Conference, LION 5","author":"Hutter"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1002\/wics.1198"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1013203451"},{"key":"ref22","article-title":"AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data","author":"Erickson","year":"2020","journal-title":"CoRR"},{"key":"ref23","article-title":"Auto-sklearn 2.0: Hands-free AutoML via meta-learning","author":"Feurer","year":"2022","journal-title":"J. Mach. Learn. Res."},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1996.tb02080.x"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2018.2867638"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1002\/widm.1484"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1214\/088342306000000060"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3298689.3347058"},{"key":"ref30","article-title":"Winner\u2019s curse? On pace, progress, and empirical rigor","volume-title":"6th International Conference on Learning Representations, ICLR 2018","author":"Sculley"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.5555\/2188385.2188395"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/BigMM50055.2020.00041"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2018.00038"},{"key":"ref34","article-title":"Hyperparameter tuning with renyi differential privacy","volume-title":"The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event","author":"Papernot"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106622"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/296"},{"key":"ref37","author":"Eggensperger","year":"2022","journal-title":"HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO"},{"key":"ref38","article-title":"AutoML-Zero: Evolving Machine Learning Algorithms From Scratch","volume-title":"Proceedings of the 37th International Conference on Machine Learning","author":"Real"},{"key":"ref39","volume-title":"Automated Machine Learning: Methods, Systems, Challenges, ser. The Springer Series on Challenges in Machine Learning","year":"2019"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2006.03.001"},{"key":"ref41","author":"Kapoor","year":"2021","journal-title":"A Simple and Fast Baseline for Tuning Large XGBoost Models"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008202821328"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1613\/jair.1.11854"},{"key":"ref44","doi-asserted-by":"crossref","DOI":"10.1145\/3644815.3644967","article-title":"Green AI: A preliminary empirical study on energy consumption in DL models across different runtime infrastructures","volume-title":"Proceedings of the IEEE\/ACM 3rd International Conference on AI Engineering - Software Engineering for AI, CAIN 2024","author":"Alizadeh"},{"key":"ref45","article-title":"AutoGluon-TimeSeries: AutoML for probabilistic time series forecasting","volume-title":"International Conference on Automated Machine Learning","author":"Shchur"},{"key":"ref46","article-title":"AutoGluon-multimodal (AutoMM): Supercharging multimodal AutoML with foundation models","volume-title":"International Conference on Automated Machine Learning","author":"Tang"},{"key":"ref47","article-title":"Causality Challenge: Benchmarking relevant signal components for effective monitoring and process control","volume-title":"Causality: Objectives and Assessment (NIPS 2008 Workshop)","author":"McCann"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-024-00934-w"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1162\/evco_a_00242"}],"event":{"name":"2025 IEEE International Conference on Data Mining Workshops (ICDMW)","location":"Washington, DC, USA","start":{"date-parts":[[2025,11,12]]},"end":{"date-parts":[[2025,11,15]]}},"container-title":["2025 IEEE International Conference on Data Mining Workshops (ICDMW)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11415623\/11415713\/11415982.pdf?arnumber=11415982","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T05:18:51Z","timestamp":1773206331000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11415982\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,12]]},"references-count":49,"URL":"https:\/\/doi.org\/10.1109\/icdmw69685.2025.00200","relation":{},"subject":[],"published":{"date-parts":[[2025,11,12]]}}}