2024
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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
|
Hollmann, Noah; Müller, Samuel; Eggensperger, Katharina; Hutter, Frank TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second Inproceedings In: The Eleventh International Conference on Learning Representations (ICLR), 2023, ( top-25% of accepted papers ). @inproceedings{hollmann2023tabpfn,
title = {TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second},
author = {Noah Hollmann and Samuel Müller and Katharina Eggensperger and Frank Hutter},
year = {2023},
booktitle = {The Eleventh International Conference on Learning Representations (ICLR)},
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 = {}
}
|
Eggensperger, Katharina Advanced Hyperparameter Optimization: Performance Modelling and Efficient Benchmarking PhD Thesis University of Freiburg, Department of Computer Science, 2022. @phdthesis{eggensperger22,
title = {Advanced Hyperparameter Optimization: Performance Modelling and Efficient Benchmarking},
author = {Katharina Eggensperger},
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 = {}
}
|
Hollmann, Noah; Müller, Samuel; Eggensperger, Katharina; Hutter, Frank TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second Inproceedings In: NeurIPS 2022 First Table Representation Workshop, 2022. @inproceedings{hollmann2022tabpfn,
title = {TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second},
author = {Noah Hollmann and Samuel Müller and Katharina Eggensperger and Frank Hutter},
year = {2022},
booktitle = {NeurIPS 2022 First Table Representation Workshop},
keywords = {}
}
|
2021
|
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 = {}
}
|
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 = {}
}
|
Eggensperger, Katharina; Haase, Kai; Müller, Philipp; Lindauer, Marius; Hutter, Frank Neural Model-based Optimization with Right-Censored Observations Journal Article In: arXiv:2009:13828 [cs.AI], 2020. @article{eggensperger-arxiv20a,
title = {Neural Model-based Optimization with Right-Censored Observations},
author = {Katharina Eggensperger and Kai Haase and Philipp Müller and Marius Lindauer and Frank Hutter},
year = {2020},
journal = {arXiv:2009:13828 [cs.AI]},
keywords = {}
}
|
2019
|
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; 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 = {}
}
|
Eggensperger, Katharina; Lindauer, Marius; Hutter, Frank Pitfalls and Best Practices in Algorithm Configuration Journal Article In: Journal of Artificial Intelligence Research (JAIR), vol. 64, pp. 861–893, 2019. @article{eggensperger-jair19a,
title = {Pitfalls and Best Practices in Algorithm Configuration},
author = {Katharina Eggensperger and Marius Lindauer and Frank Hutter},
year = {2019},
journal = {Journal of Artificial Intelligence Research (JAIR)},
volume = {64},
pages = {861--893},
keywords = {}
}
|
2018
|
Eggensperger, Katharina; Lindauer, Marius; Hutter, Frank Neural Networks for Predicting Algorithm Runtime Distributions Inproceedings In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI’18), pp. 1442-1448, 2018. @inproceedings{eggensperger-ijcai18a,
title = {Neural Networks for Predicting Algorithm Runtime Distributions},
author = {Katharina Eggensperger and Marius Lindauer and Frank Hutter},
year = {2018},
booktitle = {Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI’18)},
pages = {1442-1448},
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 = {}
}
|
Eggensperger, Katharina; Lindauer, Marius; Hoos, Holger H; Hutter, Frank; Leyton-Brown, Kevin Efficient Benchmarking of Algorithm Configurators via Model-Based Surrogates Journal Article In: Machine Learning, vol. 107, pp. 15-41, 2018. @article{eggensperger-ml18a,
title = {Efficient Benchmarking of Algorithm Configurators via Model-Based Surrogates},
author = {Katharina Eggensperger and Marius Lindauer and Holger H Hoos and Frank Hutter and Kevin Leyton-Brown},
year = {2018},
journal = {Machine Learning},
volume = {107},
pages = {15-41},
keywords = {}
}
|
2017
|
Martinez-Cantin, Ruben; Tee, Kevin; McCourt, Mike; Eggensperger, Katharina Filtering Outliers in Bayesian Optimization Inproceedings In: NeuriPS workshop on Bayesian Optimization (BayesOpt'17), 2017. @inproceedings{Cantin-BayesOpt17,
title = {Filtering Outliers in Bayesian Optimization},
author = {Ruben Martinez-Cantin and Kevin Tee and Mike McCourt and Katharina Eggensperger},
year = {2017},
booktitle = {NeuriPS workshop on Bayesian Optimization (BayesOpt'17)},
keywords = {}
}
|
Biedenkapp, André; Lindauer, Marius; Eggensperger, Katharina; Fawcett, Chris; Hoos, Holger H; Hutter, Frank Efficient Parameter Importance Analysis via Ablation with Surrogates Inproceedings In: Proceedings of the Thirty-First Conference on Artificial Intelligence (AAAI'17), pp. 773–779, 2017. @inproceedings{biedenkapp-aaai17a,
title = {Efficient Parameter Importance Analysis via Ablation with Surrogates},
author = {André Biedenkapp and Marius Lindauer and Katharina Eggensperger and Chris Fawcett and Holger H Hoos and Frank Hutter},
year = {2017},
booktitle = {Proceedings of the Thirty-First Conference on Artificial Intelligence (AAAI'17)},
pages = {773--779},
keywords = {}
}
|
Schirrmeister, Robin; Springenberg, Jost Tobias; Fiederer, Lukas; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio Deep learning with convolutional neural networks for EEG decoding and visualization Journal Article In: Human Brain Mapping, vol. 38, pp. 5391–5420, 2017. @article{schirrmeister-17a,
title = {Deep learning with convolutional neural networks for EEG decoding and visualization},
author = {Robin Schirrmeister and Jost Tobias Springenberg and Lukas Fiederer and Martin Glasstetter and Katharina Eggensperger and Michael Tangermann and Frank Hutter and Wolfram Burgard and Tonio Ball},
year = {2017},
journal = {Human Brain Mapping},
volume = {38},
pages = {5391--5420},
keywords = {}
}
|
2016
|
Meinel, Andreas; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank Hyperparameter Optimization for Machine Learning Problems in BCI (Abstract) Inproceedings In: Proceedings of the International Brain Computer Interface Meeting 2016, 2016. @inproceedings{meinel-bci16a,
title = {Hyperparameter Optimization for Machine Learning Problems in BCI (Abstract)},
author = {Andreas Meinel and Katharina Eggensperger and Michael Tangermann and Frank Hutter},
year = {2016},
booktitle = {Proceedings of the International Brain Computer Interface Meeting 2016},
keywords = {}
}
|
Schubert, Tobias; Eggensperger, Katharina; Gkogkidis, Alexis; Hutter, Frank; Ball, Tonio; Burgard, Wolfram Automatic Bone Parameter Estimation for Skeleton Tracking in Optical Motion Capture Inproceedings In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA'16), 2016, (Video showing the results of the optimization procedure). @inproceedings{schubert_icra16a,
title = {Automatic Bone Parameter Estimation for Skeleton Tracking in Optical Motion Capture},
author = {Tobias Schubert and Katharina Eggensperger and Alexis Gkogkidis and Frank Hutter and Tonio Ball and Wolfram Burgard},
year = {2016},
booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA'16)},
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 = {}
}
|
Eggensperger, K; Hutter, F; Hoos, H H; Leyton-Brown, K Efficient Benchmarking of Hyperparameter Optimizers via Surrogates Inproceedings In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015. @inproceedings{Eggensperger2015,
title = {Efficient Benchmarking of Hyperparameter Optimizers via Surrogates},
author = {K Eggensperger and F Hutter and H H Hoos and K Leyton-Brown},
year = {2015},
booktitle = {Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence},
keywords = {}
}
|
2014
|
Eggensperger, Katharina; Hutter, Frank; Hoos, Holger H; Leyton-Brown, Kevin Surrogate Benchmarks for Hyperparameter Optimization Inproceedings In: ECAI workshop on Metalearning and Algorithm Selection (MetaSel), pp. 24-31, 2014, (Superseeded by the AAAI15 paper _Efficient Benchmarking of Hyperparameter
Optimizers via Surrogates_). @inproceedings{EggHutHooLey,
title = {Surrogate Benchmarks for Hyperparameter Optimization},
author = {Katharina Eggensperger and Frank Hutter and Holger H Hoos and Kevin Leyton-Brown},
year = {2014},
booktitle = {ECAI workshop on Metalearning and Algorithm Selection (MetaSel)},
pages = {24-31},
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 = {}
}
|
