PhD Student

Katharina Eggensperger

Postal address
Institut für Informatik
Albert-Ludwigs-Universität Freiburg
Sekretariat Hutter/Maschinelles Lernen
Georges-Köhler-Allee 074
79110 Freiburg, Germany
Fax
+49 761 203-74217
Office
Building 74, Room 00-012
TwitterLinkedInGoogleScholarORCIDGitHubMarker

Short Bio

Katharina Eggensperger is a PhD student at the Machine Learning Lab at the University of Freiburg, Germany. Her research focuses on empirical performance modeling, automated machine learning and hyperparameter optimization. She has been an invited speaker at the BayesOpt workshop at NeurIPS 2016 and co-organized the AutoML workshop in 2019, 2020 and 2021.

Projects

  • HPOBench a collection of multi-fidelity hyperparameter optimization benchmarks (superseeds HPOlib)
  • auto-sklearn an automated machine learning toolkit
  • SMAC3 a Python reimplementation of the SMAC package
  • And others, see Github

Publications

2021

Lindauer, Marius; Eggensperger, Katharina; Feurer, Matthias; Biedenkapp, André; Deng, Difan; Benjamins, Carolin; Sass, René; Hutter, Frank

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization Journal Article

In: arXiv:2109.09831, 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 Journal Article

In: arXiv:2109.06716, 2021.

Feurer, Matthias; Eggensperger, Katharina; Falkner, Stefan; Lindauer, Marius; Hutter, Frank

Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning Journal Article

In: arXiv:2007.04074, 2021.

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.).

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.

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.

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.

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.

Eggensperger, Katharina; Lindauer, Marius; Hutter, Frank

Pitfalls and Best Practices in Algorithm Configuration Journal Article

In: Journal of Artificial Intelligence Research (JAIR), 64 , pp. 861–893, 2019.

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.

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.

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, 107 , pp. 15-41, 2018.

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.

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.

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, 38 , pp. 5391–5420, 2017.

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.

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).

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.

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.

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.

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_).

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.).