Katharina Eggensperger

42 papers A* 6A 1B 1Journal 28Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Best Practices For Empirical Meta-Algorithmic Research: Guidelines from the COSEAL Research Network. CoRR Theresa Eimer, Lennart Schäpermeier, André Biedenkapp, Alexander Tornede, Lars Kotthoff, Pieter Leyman, Matthias Feurer, Katharina Eggensperger, Kaitlin Maile, Tanja Tornede, Anna Kozak, Ke Xue, Marcel Wever, Mitra Baratchi, Damir Pulatov, Heike Trautmann, Haniye Kashgarani, Marius Lindauer
2025	A	`conf`	In-Context Decision Making for Optimizing Complex AutoML Pipelines. ECAI Amir Rezaei Balef, Katharina Eggensperger
2025	J	`jnl`	In-Context Decision Making for Optimizing Complex AutoML Pipelines. CoRR Amir Rezaei Balef, Katharina Eggensperger
2025	J	`jnl`	Put CASH on Bandits: A Max K-Armed Problem for Automated Machine Learning. CoRR Amir Rezaei Balef, Claire Vernade, Katharina Eggensperger
2025	J	`jnl`	TabPFN-Wide: Continued Pre-Training for Extreme Feature Counts. CoRR Christopher Kolberg, Katharina Eggensperger, Nico Pfeifer
2025	J	`jnl`	Towards Understanding Layer Contributions in Tabular In-Context Learning Models. CoRR Amir Rezaei Balef, Mykhailo Koshil, Katharina Eggensperger
2025	J	`jnl`	carps: A Framework for Comparing N Hyperparameter Optimizers on M Benchmarks. CoRR Carolin Benjamins, Helena Graf, Sarah Segel, Difan Deng, Tim Ruhkopf, Leona Hennig, Soham Basu, Neeratyoy Mallik, Edward Bergman, Deyao Chen, François Clément, Matthias Feurer, Katharina Eggensperger, Frank Hutter, Carola Doerr, Marius Lindauer
2024	J	`jnl`	AMLTK: A Modular AutoML Toolkit in Python. J. Open Source Softw. Edward Bergman, Matthias Feurer, Aron Bahram, Amir Rezaei Balef, Lennart Purucker, Sarah Segel, Marius Lindauer, Frank Hutter, Katharina Eggensperger
2024	J	`jnl`	Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML. J. Artif. Intell. Res. Hilde J. P. Weerts, Florian Pfisterer, Matthias Feurer, Katharina Eggensperger, Edward Bergman, Noor H. Awad, Joaquin Vanschoren, Mykola Pechenizkiy, Bernd Bischl, Frank Hutter
2024	—	`ed.`	International Conference on Automated Machine Learning, 9-12 September 2024, Sorbonne Université, Paris, France. AutoML Katharina Eggensperger, Roman Garnett, Joaquin Vanschoren, Marius Lindauer, Jacob R. Gardner
2024	A*	`conf`	Position: Why We Must Rethink Empirical Research in Machine Learning. ICML Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger, Giuseppe Casalicchio, Marcel Wever, Matthias Feurer, David Rügamer, Eyke Hüllermeier, Anne-Laure Boulesteix, Bernd Bischl
2024	J	`jnl`	Position: Why We Must Rethink Empirical Research in Machine Learning. CoRR Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger, Giuseppe Casalicchio, Marcel Wever, Matthias Feurer, David Rügamer, Eyke Hüllermeier, Anne-Laure Boulesteix, Bernd Bischl
2023	J	`jnl`	Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML. CoRR Hilde J. P. Weerts, Florian Pfisterer, Matthias Feurer, Katharina Eggensperger, Edward Bergman, Noor H. Awad, Joaquin Vanschoren, Mykola Pechenizkiy, Bernd Bischl, Frank Hutter
2023	B	`conf`	Mind the Gap: Measuring Generalization Performance Across Multiple Objectives. IDA Matthias Feurer, Katharina Eggensperger, Edward Bergman, Florian Pfisterer, Bernd Bischl, Frank Hutter
2023	A*	`conf`	TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second. ICLR Noah Hollmann, Samuel Müller, Katharina Eggensperger, Frank Hutter
2022	—	`—`	Advanced hyperparameter optimization: performance modelling and efficient benchmarking. Katharina Eggensperger
2022	J	`jnl`	Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning. J. Mach. Learn. Res. Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer, Frank Hutter
2022	J	`jnl`	Meta-Learning a Real-Time Tabular AutoML Method For Small Data. CoRR Noah Hollmann, Samuel Müller, Katharina Eggensperger, Frank Hutter
2022	J	`jnl`	Mind the Gap: Measuring Generalization Performance Across Multiple Objectives. CoRR Matthias Feurer, Katharina Eggensperger, Edward Bergman, Florian Pfisterer, Bernd Bischl, Frank Hutter
2022	J	`jnl`	SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization. J. Mach. Learn. Res. Marius Lindauer, Katharina Eggensperger, Matthias Feurer, André Biedenkapp, Difan Deng, Carolin Benjamins, Tim Ruhkopf, René Sass, Frank Hutter
2021	—	`conf`	HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO. NeurIPS Datasets and Benchmarks Katharina Eggensperger, Philipp Müller, Neeratyoy Mallik, Matthias Feurer, René Sass, Aaron Klein, Noor H. Awad, Marius Lindauer, Frank Hutter
2021	J	`jnl`	HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO. CoRR Katharina Eggensperger, Philipp Müller, Neeratyoy Mallik, Matthias Feurer, René Sass, Aaron Klein, Noor H. Awad, Marius Lindauer, Frank Hutter
2021	J	`jnl`	SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization. CoRR Marius Lindauer, Katharina Eggensperger, Matthias Feurer, André Biedenkapp, Difan Deng, Carolin Benjamins, René Sass, Frank Hutter
2020	J	`jnl`	Auto-Sklearn 2.0: The Next Generation. CoRR Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer, Frank Hutter
2020	J	`jnl`	Neural Model-based Optimization with Right-Censored Observations. CoRR Katharina Eggensperger, Kai Haase, Philipp Müller, Marius Lindauer, Frank Hutter
2020	J	`jnl`	Squirrel: A Switching Hyperparameter Optimizer. CoRR Noor H. Awad, Gresa Shala, Difan Deng, Neeratyoy Mallik, Matthias Feurer, Katharina Eggensperger, André Biedenkapp, Diederick Vermetten, Hao Wang, Carola Doerr, Marius Lindauer, Frank Hutter
2019	—	`ch.`	Auto-sklearn: Efficient and Robust Automated Machine Learning. Automated Machine Learning Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Tobias Springenberg, Manuel Blum, Frank Hutter
2019	J	`jnl`	BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters. CoRR Marius Lindauer, Katharina Eggensperger, Matthias Feurer, André Biedenkapp, Joshua Marben, Philipp Müller, Frank Hutter
2019	J	`jnl`	Pitfalls and Best Practices in Algorithm Configuration. J. Artif. Intell. Res. Katharina Eggensperger, Marius Lindauer, Frank Hutter
2019	J	`jnl`	Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters. CoRR Marius Lindauer, Matthias Feurer, Katharina Eggensperger, André Biedenkapp, Frank Hutter
2018	J	`jnl`	Efficient benchmarking of algorithm configurators via model-based surrogates. Mach. Learn. Katharina Eggensperger, Marius Lindauer, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown
2018	A*	`conf`	Neural Networks for Predicting Algorithm Runtime Distributions. IJCAI Katharina Eggensperger, Marius Lindauer, Frank Hutter
2017	J	`jnl`	Deep learning with convolutional neural networks for brain mapping and decoding of movement-related information from the human EEG. CoRR Robin Tibor Schirrmeister, Jost Tobias Springenberg, Lukas Dominique Josef Fiederer, Martin Glasstetter, Katharina Eggensperger, Michael Tangermann, Frank Hutter, Wolfram Burgard, Tonio Ball
2017	J	`jnl`	Deep learning with convolutional neural networks for decoding and visualization of EEG pathology. CoRR Robin Tibor Schirrmeister, Lukas Gemein, Katharina Eggensperger, Frank Hutter, Tonio Ball
2017	J	`jnl`	Efficient Benchmarking of Algorithm Configuration Procedures via Model-Based Surrogates. CoRR Katharina Eggensperger, Marius Lindauer, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown
2017	A*	`conf`	Efficient Parameter Importance Analysis via Ablation with Surrogates. AAAI Andre Biedenkapp, Marius Lindauer, Katharina Eggensperger, Frank Hutter, Chris Fawcett, Holger H. Hoos
2017	J	`jnl`	Pitfalls and Best Practices in Algorithm Configuration. CoRR Katharina Eggensperger, Marius Lindauer, Frank Hutter
2017	J	`jnl`	Predicting Runtime Distributions using Deep Neural Networks. CoRR Katharina Eggensperger, Marius Lindauer, Frank Hutter
2016	A*	`conf`	Automatic bone parameter estimation for skeleton tracking in optical motion capture. ICRA Tobias Schubert, Katharina Eggensperger, Alexis Gkogkidis, Frank Hutter, Tonio Ball, Wolfram Burgard
2015	A*	`conf`	Efficient Benchmarking of Hyperparameter Optimizers via Surrogates. AAAI Katharina Eggensperger, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown
2015	—	`conf`	Efficient and Robust Automated Machine Learning. NIPS Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Tobias Springenberg, Manuel Blum, Frank Hutter
2014	—	`conf`	Surrogate Benchmarks for Hyperparameter Optimization. MetaSel@ECAI Katharina Eggensperger, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown