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Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges

, , , , , , , , , , , and . Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, (Mar 10, 2023)Funding Information: Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology, Grant/Award Number: BAYERN DIGITAL II; Bundesministerium für Bildung und Forschung, Grant/Award Number: 01IS18036A; Deutsche Forschungsgemeinschaft (Collaborative Research Center), Grant/Award Number: SFB 876‐A3; Federal Statistical Office of Germany; Research Center “Trustworthy Data Science and Security” Funding information Funding Information: The authors of this work take full responsibilities for its content. This work was supported by the Federal Statistical Office of Germany; the Deutsche Forschungsgemeinschaft (DFG) within the Collaborative Research Center SFB 876, A3; the Research Center “Trustworthy Data Science and Security”, one of the Research Alliance centers within the https://uaruhr.de ; the German Federal Ministry of Education and Research (BMBF) under Grant No. 01IS18036A; and the Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology through the Center for Analytics‐Data‐Applications (ADA‐Center) within the framework of “BAYERN DIGITAL II.”.
DOI: 10.1002/widm.1484

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Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models., , and . GECCO, page 538-547. ACM, (2023)Multi-objective hyperparameter tuning and feature selection using filter ensembles., , , and . GECCO, page 471-479. ACM, (2020)Deep Semi-supervised Learning for Time Series Classification., , , , , and . ICMLA, page 422-428. IEEE, (2021)Wearable-Based Parkinson's Disease Severity Monitoring Using Deep Learning., , , , , and . ECML/PKDD (3), volume 11908 of Lecture Notes in Computer Science, page 400-415. Springer, (2019)Structured Verification of Machine Learning Models in Industrial Settings., , , , and . Big Data, 11 (3): 181-198 (June 2023)FusionKit: a generic toolkit for skeleton, marker and rigid-body tracking., , , and . EICS, page 73-84. ACM, (2016)Tackling Neural Architecture Search With Quality Diversity Optimization., , , , , and . AutoML, volume 188 of Proceedings of Machine Learning Research, page 9/1-30. PMLR, (2022)Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges, , , , , , , , , and 2 other author(s). Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, (Mar 10, 2023)Funding Information: Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology, Grant/Award Number: BAYERN DIGITAL II; Bundesministerium für Bildung und Forschung, Grant/Award Number: 01IS18036A; Deutsche Forschungsgemeinschaft (Collaborative Research Center), Grant/Award Number: SFB 876‐A3; Federal Statistical Office of Germany; Research Center “Trustworthy Data Science and Security” Funding information Funding Information: The authors of this work take full responsibilities for its content. This work was supported by the Federal Statistical Office of Germany; the Deutsche Forschungsgemeinschaft (DFG) within the Collaborative Research Center SFB 876, A3; the Research Center “Trustworthy Data Science and Security”, one of the Research Alliance centers within the https://uaruhr.de ; the German Federal Ministry of Education and Research (BMBF) under Grant No. 01IS18036A; and the Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology through the Center for Analytics‐Data‐Applications (ADA‐Center) within the framework of “BAYERN DIGITAL II.”.mlrMBO: A modular framework for model-based optimization of expensive black-box functions, , , , , and . arXiv preprint arXiv:1703.03373, (2017)A collection of quality diversity optimization problems derived from hyperparameter optimization of machine learning models., , , and . GECCO Companion, page 2136-2142. ACM, (2022)