2024
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Lindauer, Marius; Karl, Florian; Klier, Anne; Moosbauer, Julia; Tornede, Alexander; Mueller, Andreas C; Hutter, Frank; Feurer, Matthias; Bischl, Bernd Position: A Call to Action for a Human-Centered AutoML Paradigm Inproceedings In: Proceedings of the 41st International Conference on Machine Learning (ICML), 2024. @inproceedings{Lindauer2024,
title = {Position: A Call to Action for a Human-Centered AutoML Paradigm},
author = {Marius Lindauer and Florian Karl and Anne Klier and Julia Moosbauer and Alexander Tornede and Andreas C Mueller and Frank Hutter and Matthias Feurer and Bernd Bischl},
year = {2024},
booktitle = {Proceedings of the 41st International Conference on Machine Learning (ICML)},
keywords = {}
}
|
Kohli, Ravin; Feurer, Matthias; Eggensperger, Katharina; Bischl, Bernd; Hutter, Frank Towards Quantifying the Effect of Datasets for Benchmarking: A Look at Tabular Machine Learning Inproceedings In: Data-centric Machine Learning Research (DMLR) Workshop (ICLR 2024), 2024. @inproceedings{Kohli2024,
title = {Towards Quantifying the Effect of Datasets for Benchmarking: A Look at Tabular Machine Learning},
author = {Ravin Kohli and Matthias Feurer and Katharina Eggensperger and Bernd Bischl and Frank Hutter},
year = {2024},
booktitle = {Data-centric Machine Learning Research (DMLR) Workshop (ICLR 2024)},
journal = {Data-centric Machine Learning Research (DMLR) Workshop at ICLR},
keywords = {}
}
|
Bergman, Edward; Feurer, Matthias; Bahram, Aron; Balef, Amir Rezaei; Purucker, Lennart; Segel, Sarah; Lindauer, Marius; Hutter, Frank; Eggensperger, Katharina AMLTK: A Modular AutoML Toolkit in Python Journal Article In: Journal of Open Source Software, vol. 9, no. 100, pp. 6367, 2024. @article{bergman2024amltk,
title = {AMLTK: A Modular AutoML Toolkit in Python},
author = {Edward Bergman and Matthias Feurer and Aron Bahram and Amir Rezaei Balef and Lennart Purucker and Sarah Segel and Marius Lindauer and Frank Hutter and Katharina Eggensperger},
year = {2024},
journal = {Journal of Open Source Software},
volume = {9},
number = {100},
pages = {6367},
keywords = {}
}
|
2023
|
Müller, Samuel; Feurer, Matthias; Hollmann, Noah; Hutter, Frank PFNs4BO: In-Context Learning for Bayesian Optimization Inproceedings In: Proceedings of the 40th International Conference on Machine Learning (ICML 2023), 2023. @inproceedings{sam_at_icml23,
title = {PFNs4BO: In-Context Learning for Bayesian Optimization},
author = {Samuel Müller and Matthias Feurer and Noah Hollmann and Frank Hutter},
year = {2023},
booktitle = {Proceedings of the 40th International Conference on Machine Learning (ICML 2023)},
keywords = {}
}
|
Feurer, Matthias; Eggensperger, Katharina; Bergman, Edward; Pfisterer, Florian; Bischl, Bernd; Hutter, Frank Mind the Gap: Measuring Generalization Performance Across Multiple Objectives Inproceedings In: Crémilleux, Bruno; Hess, Sibylle; Nijssen, Siegfried (Ed.): Advances in Intelligent Data Analysis XXI. IDA 2023., pp. 130-142, Springer, Cham, 2023. @inproceedings{feurer-ida23a,
title = {Mind the Gap: Measuring Generalization Performance Across Multiple Objectives},
author = {Matthias Feurer and Katharina Eggensperger and Edward Bergman and Florian Pfisterer and Bernd Bischl and Frank Hutter},
editor = {Crémilleux, Bruno and Hess, Sibylle and Nijssen, Siegfried},
doi = {https://doi.org/10.1007/978-3-031-30047-9_11},
year = {2023},
booktitle = {Advances in Intelligent Data Analysis XXI. IDA 2023.},
volume = {13876},
pages = {130-142},
publisher = {Springer, Cham},
series = {Lecture Notes in Computer Science},
keywords = {}
}
|
Weerts, Hilde; Pfisterer, Florian; Feurer, Matthias; Eggensperger, Katharina; Bergman, Edward; Awad, Noor; Vanschoren, Joaquin; Pechenizkiy, Mykola; Bischl, Bernd; Hutter, Frank Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML Journal Article In: arXiv:2303.08485 [cs.AI], 2023. @article{weerts-arxiv23a,
title = {Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML},
author = {Hilde Weerts and Florian Pfisterer and Matthias Feurer and Katharina Eggensperger and Edward Bergman and Noor Awad and Joaquin Vanschoren and Mykola Pechenizkiy and Bernd Bischl and Frank Hutter},
year = {2023},
journal = {arXiv:2303.08485 [cs.AI]},
keywords = {}
}
|
2022
|
Feurer, Matthias; Eggensperger, Katharina; Falkner, Stefan; Lindauer, Marius; Hutter, Frank Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning Journal Article In: Journal of Machine Learning Research, vol. 23, no. 261, pp. 1-61, 2022. @article{feurer-jmlr22a,
title = {Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning},
author = {Matthias Feurer and Katharina Eggensperger and Stefan Falkner and Marius Lindauer and Frank Hutter},
editor = {Marc Schoenauer},
year = {2022},
journal = {Journal of Machine Learning Research},
volume = {23},
number = {261},
pages = {1-61},
keywords = {}
}
|
Feurer, Matthias Robust and Efficient Automated Machine Learning: Systems, Infrastructure and Advances in Hyperparameter Optimization PhD Thesis University of Freiburg, Department of Computer Science, 2022. @phdthesis{feurer22,
title = {Robust and Efficient Automated Machine Learning: Systems, Infrastructure and Advances in Hyperparameter Optimization},
author = {Matthias Feurer},
year = {2022},
address = {Freiburg, Germany},
school = {University of Freiburg, Department of Computer Science},
keywords = {}
}
|
Lindauer, Marius; Eggensperger, Katharina; Feurer, Matthias; Biedenkapp, André; Deng, Difan; Benjamins, Carolin; Ruhkopf, Tim; Sass, René; Hutter, Frank SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization Journal Article In: Journal of Machine Learning Research (JMLR) -- MLOSS, vol. 23, no. 54, pp. 1-9, 2022. @article{lindauer-jmlr22a,
title = { SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization},
author = {Marius Lindauer and Katharina Eggensperger and Matthias Feurer and André Biedenkapp and Difan Deng and Carolin Benjamins and Tim Ruhkopf and René Sass and Frank Hutter},
year = {2022},
journal = {Journal of Machine Learning Research (JMLR) -- MLOSS},
volume = {23},
number = {54},
pages = {1-9},
keywords = {}
}
|
Feurer, Matthias; Letham, Benjamin; Hutter, Frank; Bakshy, Eytan Practical Transfer Learning for Bayesian Optimization Journal Article In: arXiv:1802:02219v3 [stat.ML], 2022. @article{feurer-arxiv22a,
title = {Practical Transfer Learning for Bayesian Optimization},
author = {Matthias Feurer and Benjamin Letham and Frank Hutter and Eytan Bakshy },
year = {2022},
journal = {arXiv:1802:02219v3 [stat.ML]},
keywords = {}
}
|
Müller, Samuel; Arango, Sebastian Pineda; Feurer, Matthias; Grabocka, Josif; Hutter, Frank Bayesian Optimization with a Neural Network Meta-learned on Synthetic Data Only Workshop Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, 2022. @workshop{müller2022bayesian,
title = {Bayesian Optimization with a Neural Network Meta-learned on Synthetic Data Only},
author = {Samuel Müller and Sebastian Pineda Arango and Matthias Feurer and Josif Grabocka and Frank Hutter},
year = {2022},
booktitle = {Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems},
keywords = {}
}
|
2021
|
Bischl, Bernd; Casalicchio, Giuseppe; Feurer, Matthias; Gijsbers, Pieter; Hutter, Frank; Lang, Michel; Mantovani, Rafael G; van Rijn, Jan N; Vanschoren, Joaquin OpenML Benchmarking Suites Inproceedings In: Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks, 2021. @inproceedings{bischl-neurips21a,
title = {OpenML Benchmarking Suites },
author = {Bernd Bischl and Giuseppe Casalicchio and Matthias Feurer and Pieter Gijsbers and Frank Hutter and Michel Lang and Rafael G Mantovani and Jan N van Rijn and Joaquin Vanschoren},
year = {2021},
booktitle = {Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks},
keywords = {}
}
|
Eggensperger, Katharina; Müller, Philipp; Mallik, Neeratyoy; Feurer, Matthias; Sass, René; Klein, Aaron; Awad, Noor; Lindauer, Marius; Hutter, Frank HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO Inproceedings In: Vanschoren, J.; Yeung, S. (Ed.): Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks, 2021. @inproceedings{eggensperger-neuripsdbt21,
title = {HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO},
author = {Katharina Eggensperger and Philipp Müller and Neeratyoy Mallik and Matthias Feurer and René Sass and Aaron Klein and Noor Awad and Marius Lindauer and Frank Hutter},
editor = {J. Vanschoren and S. Yeung},
year = {2021},
booktitle = {Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks},
journal = {arXiv:2109.06716},
volume = {1},
keywords = {}
}
|
Feurer, Matthias; van Rijn, Jan N; Kadra, Arlind; Gijsbers, Pieter; Mallik, Neeratyoy; Ravi, Sahithya; Müller, Andreas; Vanschoren, Joaquin; Hutter, Frank OpenML-Python: an extensible Python API for OpenML Journal Article In: Journal of Machine Learning Research, vol. 22, no. 100, pp. 1-5, 2021. @article{feurer-jmlr21a,
title = {OpenML-Python: an extensible Python API for OpenML},
author = {Matthias Feurer and Jan N van Rijn and Arlind Kadra and Pieter Gijsbers and Neeratyoy Mallik and Sahithya Ravi and Andreas Müller and Joaquin Vanschoren and Frank Hutter},
year = {2021},
journal = {Journal of Machine Learning Research},
volume = {22},
number = {100},
pages = {1-5},
keywords = {}
}
|
2020
|
Awad, Noor; Shala, Gresa; Deng, Difan; Mallik, Neeratyoy; Feurer, Matthias; Eggensperger, Katharina; Biedenkapp, André; Vermetten, Diederick; Wang, Hao; Doerr, Carola; Lindauer, Marius; Hutter, Frank Squirrel: A Switching Hyperparameter Optimizer Description of the entry by AutoML.org & IOHprofiler to the NeurIPS 2020 BBO challenge Journal Article In: arXiv:2012.08180 [cs.LG], 2020, (Optimizer description for the NeurIPS 2020 BBO
competition.
Squirrel won the competition´s warm-starting friendly
leaderboard.). @article{awad-arxiv20a,
title = {Squirrel: A Switching Hyperparameter Optimizer Description of the entry by AutoML.org & IOHprofiler to the NeurIPS 2020 BBO challenge},
author = {Noor Awad and Gresa Shala and Difan Deng and Neeratyoy Mallik and Matthias Feurer and Katharina Eggensperger and André Biedenkapp and Diederick Vermetten and Hao Wang and Carola Doerr and Marius Lindauer and Frank Hutter},
year = {2020},
journal = {arXiv:2012.08180 [cs.LG]},
keywords = {}
}
|
2019
|
Bischl, Bernd; Casalicchio, Giuseppe; Feurer, Matthias; Hutter, Frank; Lang, Michel; Mantovani, Rafael G; van Rijn, Jan N; Vanschoren, Joaquin OpenML Benchmarking Suites Journal Article In: arXiv, vol. 1708.0373v2, pp. 1-6, 2019. @article{bischl-arxiv19a,
title = {OpenML Benchmarking Suites},
author = {Bernd Bischl and Giuseppe Casalicchio and Matthias Feurer and Frank Hutter and Michel Lang and Rafael G Mantovani and Jan N van Rijn and Joaquin Vanschoren},
year = {2019},
journal = {arXiv},
volume = {1708.0373v2},
pages = {1-6},
keywords = {}
}
|
Lindauer, Marius; Eggensperger, Katharina; Feurer, Matthias; Biedenkapp, André; Marben, Joshua; Müller, Philipp; Hutter, Frank BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters Journal Article In: arXiv:1908.06756 [cs.LG], 2019. @article{lindauer-arxiv19,
title = {BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters},
author = {Marius Lindauer and Katharina Eggensperger and Matthias Feurer and André Biedenkapp and Joshua Marben and Philipp Müller and Frank Hutter},
year = {2019},
journal = {arXiv:1908.06756 [cs.LG]},
keywords = {}
}
|
Lindauer, Marius; Feurer, Matthias; Eggensperger, Katharina; Biedenkapp, André; Hutter, Frank Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters Inproceedings In: IJCAI 2019 DSO Workshop, 2019. @inproceedings{lindauer-dso19,
title = {Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters},
author = {Marius Lindauer and Matthias Feurer and Katharina Eggensperger and André Biedenkapp and Frank Hutter},
year = {2019},
booktitle = {IJCAI 2019 DSO Workshop},
keywords = {}
}
|
Feurer, Matthias; Hutter, Frank Hyperparameter Optimization Incollection In: Hutter, Frank; Kotthoff, Lars; Vanschoren, Joaquin (Ed.): AutoML: Methods, Sytems, Challenges, pp. 3–33, Springer, 2019. @incollection{feurer-automlbook19a,
title = {Hyperparameter Optimization},
author = {Matthias Feurer and Frank Hutter},
editor = {Frank Hutter and Lars Kotthoff and Joaquin Vanschoren},
year = {2019},
booktitle = {AutoML: Methods, Sytems, Challenges},
pages = {3--33},
publisher = {Springer},
chapter = {1},
keywords = {}
}
|
Feurer, Matthias; Klein, Aaron; Eggensperger, Katharina; Springenberg, Jost; Blum, Manuel; Hutter, Frank Auto-sklearn: Efficient and Robust Automated Machine Learning Incollection In: Hutter, Frank; Kotthoff, Lars; Vanschoren, Joaquin (Ed.): AutoML: Methods, Systems, Challenges, pp. 113–134, Springer, 2019. @incollection{feurer-automlbook19b,
title = {Auto-sklearn: Efficient and Robust Automated Machine Learning},
author = {Matthias Feurer and Aaron Klein and Katharina Eggensperger and Jost Springenberg and Manuel Blum and Frank Hutter},
editor = {Frank Hutter and Lars Kotthoff and Joaquin Vanschoren},
doi = {10.1007/978-3-030-05318-5_6},
year = {2019},
booktitle = {AutoML: Methods, Systems, Challenges},
pages = {113--134},
publisher = {Springer},
chapter = {6},
keywords = {}
}
|
Mendoza, Hector; Klein, Aaron; Feurer, Matthias; Springenberg, Jost Tobias; Urban, Matthias; Burkart, Michael; Dippel, Max; Lindauer, Marius; Hutter, Frank Towards Automatically-Tuned Deep Neural Networks Incollection In: Hutter, Frank; Kotthoff, Lars; Vanschoren, Joaquin (Ed.): AutoML: Methods, Sytems, Challenges, pp. 135–149, Springer, 2019. @incollection{mendoza-automlbook19a,
title = {Towards Automatically-Tuned Deep Neural Networks},
author = {Hector Mendoza and Aaron Klein and Matthias Feurer and Jost Tobias Springenberg and Matthias Urban and Michael Burkart and Max Dippel and Marius Lindauer and Frank Hutter},
editor = {Frank Hutter and Lars Kotthoff and Joaquin Vanschoren},
year = {2019},
booktitle = {AutoML: Methods, Sytems, Challenges},
pages = {135--149},
publisher = {Springer},
chapter = {7},
keywords = {}
}
|
2018
|
Feurer, Matthias; Letham, Benjamin; Bakshy, Eytan Scalable Meta-Learning for Bayesian Optimization using Ranking-Weighted Gaussian Process Ensembles Inproceedings In: ICML 2018 AutoML Workshop, 2018, (This publication is superseded by the 2022 arXiv preprint Practical Transfer Learning for Bayesian Optimization.). @inproceedings{feurer-automl18c,
title = {Scalable Meta-Learning for Bayesian Optimization using Ranking-Weighted Gaussian Process Ensembles},
author = {Matthias Feurer and Benjamin Letham and Eytan Bakshy},
year = {2018},
booktitle = {ICML 2018 AutoML Workshop},
keywords = {}
}
|
Feurer, Matthias; Eggensperger, Katharina; Falkner, Stefan; Lindauer, Marius; Hutter, Frank Practical Automated Machine Learning for the AutoML Challenge 2018 Inproceedings In: ICML 2018 AutoML Workshop, 2018. @inproceedings{feurer-automl18b,
title = {Practical Automated Machine Learning for the AutoML Challenge 2018},
author = {Matthias Feurer and Katharina Eggensperger and Stefan Falkner and Marius Lindauer and Frank Hutter},
year = {2018},
booktitle = {ICML 2018 AutoML Workshop},
keywords = {}
}
|
Feurer, M; Hutter, F Towards Further Automation in AutoML Inproceedings In: ICML 2018 AutoML Workshop, 2018. @inproceedings{feurer-automl18a,
title = {Towards Further Automation in AutoML},
author = {M Feurer and F Hutter},
year = {2018},
booktitle = {ICML 2018 AutoML Workshop},
keywords = {}
}
|
2017
|
Bischl, Bernd; Casalicchio, Giuseppe; Feurer, Matthias; Hutter, Frank; Lang, Michel; Mantovani, Rafael G; van Rijn, Jan N; Vanschoren, Joaquin OpenML Benchmarking Suites and the OpenML100 Journal Article In: arXiv, vol. 1708.0373v1, pp. 1-6, 2017. @article{bischl-arxiv17a,
title = {OpenML Benchmarking Suites and the OpenML100},
author = {Bernd Bischl and Giuseppe Casalicchio and Matthias Feurer and Frank Hutter and Michel Lang and Rafael G Mantovani and Jan N van Rijn and Joaquin Vanschoren},
year = {2017},
journal = {arXiv},
volume = {1708.0373v1},
pages = {1-6},
keywords = {}
}
|
2016
|
Mendoza, H; Klein, A; Feurer, M; Springenberg, J; Hutter, F Towards Automatically-Tuned Neural Networks Inproceedings In: ICML 2016 AutoML Workshop, 2016. @inproceedings{mendoza-automl16a,
title = {Towards Automatically-Tuned Neural Networks},
author = {H Mendoza and A Klein and M Feurer and J Springenberg and F Hutter},
year = {2016},
booktitle = {ICML 2016 AutoML Workshop},
keywords = {}
}
|
2015
|
Feurer, Matthias; Klein, Aaron; Eggensperger, Katharina; Springenberg, Jost Tobias; Blum, Manuel; Hutter, Frank Efficient and Robust Automated Machine Learning Inproceedings In: Advances in Neural Information Processing Systems 28 (NeurIPS'15), pp. 2962–2970, 2015. @inproceedings{feurer-neurip2015,
title = {Efficient and Robust Automated Machine Learning},
author = {Matthias Feurer and Aaron Klein and Katharina Eggensperger and Jost Tobias Springenberg and Manuel Blum and Frank Hutter},
year = {2015},
booktitle = {Advances in Neural Information Processing Systems 28 (NeurIPS'15)},
pages = {2962--2970},
keywords = {}
}
|
Feurer, Matthias; Klein, Aaron; Eggensperger, Katharina; Springenberg, Jost Tobias; Blum, Manuel; Hutter, Frank Methods for Improving Bayesian Optimization for AutoML Inproceedings In: ICML 2015 AutoML Workshop, 2015. @inproceedings{feurer-automl15a,
title = {Methods for Improving Bayesian Optimization for AutoML},
author = {Matthias Feurer and Aaron Klein and Katharina Eggensperger and Jost Tobias Springenberg and Manuel Blum and Frank Hutter},
year = {2015},
booktitle = {ICML 2015 AutoML Workshop},
keywords = {}
}
|
Vanschoren, J; van Rijn, J; Bischl, B; Casalicchio, G; Lang, M; Feurer, M OpenML: a Networked Science Platform for Machine Learning (Abstract) Inproceedings In: ICML 2015 MLOSS Workshop, 2015. @inproceedings{vanschoren-mloss15a,
title = {OpenML: a Networked Science Platform for Machine Learning (Abstract)},
author = {J Vanschoren and J van Rijn and B Bischl and G Casalicchio and M Lang and M Feurer},
year = {2015},
booktitle = {ICML 2015 MLOSS Workshop},
keywords = {}
}
|
Feurer, M; Springenberg, T; Hutter, F Initializing Bayesian Hyperparameter Optimization via Meta-Learning Inproceedings In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015. @inproceedings{Feurer2015,
title = {Initializing Bayesian Hyperparameter Optimization via Meta-Learning},
author = {M Feurer and T Springenberg and F Hutter},
year = {2015},
booktitle = {Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence},
keywords = {}
}
|
2014
|
Feurer, M; Springenberg, T; Hutter, F Using Meta-Learning to Initialize Bayesian Optimization of Hyperparameters Inproceedings In: ECAI workshop on Metalearning and Algorithm Selection (MetaSel), pp. 3–10, 2014, (Superseeded by the AAAI15 paper _Initializing Bayesian Hyperparameter
Optimization via Meta-Learning_). @inproceedings{FeuSprHut,
title = {Using Meta-Learning to Initialize Bayesian Optimization of Hyperparameters},
author = {M Feurer and T Springenberg and F Hutter},
year = {2014},
booktitle = {ECAI workshop on Metalearning and Algorithm Selection (MetaSel)},
pages = {3--10},
keywords = {}
}
|
2013
|
Eggensperger, Katharina; Feurer, Matthias; Hutter, Frank; Bergstra, James; Snoek, Jasper; Hoos, Holger H; Leyton-Brown, Kevin Towards an Empirical Foundation for Assessing Bayesian Optimization of Hyperparameters Inproceedings In: NeurIPS workshop on Bayesian Optimization in Theory and Practice, 2013, (Software and benchmarks are available from our HPOlib website.). @inproceedings{eggensperger-bayesopt13a,
title = {Towards an Empirical Foundation for Assessing Bayesian Optimization of Hyperparameters},
author = {Katharina Eggensperger and Matthias Feurer and Frank Hutter and James Bergstra and Jasper Snoek and Holger H Hoos and Kevin Leyton-Brown},
year = {2013},
booktitle = {NeurIPS workshop on Bayesian Optimization in Theory and Practice},
keywords = {}
}
|
