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2020 – today
- 2024
[c4]Marius Lindauer, Florian Karl, Anne Klier, Julia Moosbauer, Alexander Tornede, Andreas Müller, Frank Hutter, Matthias Feurer, Bernd Bischl:
Position: A Call to Action for a Human-Centered AutoML Paradigm. ICML 2024- [i10]Marius Lindauer, Florian Karl, Anne Klier, Julia Moosbauer, Alexander Tornede, Andreas Mueller, Frank Hutter, Matthias Feurer, Bernd Bischl:
Position: A Call to Action for a Human-Centered AutoML Paradigm. CoRR abs/2406.03348 (2024) - 2023
- [b1]Julia Moosbauer:
Towards explainable automated machine learning. Ludwig Maximilian University of Munich, Germany, 2023 - [j2]Florian Karl
, Tobias Pielok, Julia Moosbauer, Florian Pfisterer, Stefan Coors, Martin Binder, Lennart Schneider, Janek Thomas, Jakob Richter, Michel Lang, Eduardo C. Garrido-Merchán, Jürgen Branke, Bernd Bischl:
Multi-Objective Hyperparameter Optimization in Machine Learning - An Overview. ACM Trans. Evol. Learn. Optim. 3(4): 16:1-16:50 (2023) - [i9]M. Jorge Cardoso, Julia Moosbauer, Tessa Sundaram Cook, Barbaros Selnur Erdal, Brad W. Genereaux, Vikash Gupta, Bennett A. Landman, Tiarna Lee, Parashkev Nachev, Elanchezhian Somasundaram, Ronald M. Summers, Khaled Younis, Sébastien Ourselin, Franz Pfister:
RAISE - Radiology AI Safety, an End-to-end lifecycle approach. CoRR abs/2311.14570 (2023) - [i8]Christian A. Scholbeck, Julia Moosbauer, Giuseppe Casalicchio, Hoshin Gupta, Bernd Bischl, Christian Heumann:
Position Paper: Bridging the Gap Between Machine Learning and Sensitivity Analysis. CoRR abs/2312.13234 (2023) - 2022
- [j1]Julia Moosbauer, Martin Binder, Lennart Schneider, Florian Pfisterer, Marc Becker, Michel Lang, Lars Kotthoff, Bernd Bischl:
Automated Benchmark-Driven Design and Explanation of Hyperparameter Optimizers. IEEE Trans. Evol. Comput. 26(6): 1336-1350 (2022) - [c3]Florian Pfisterer, Lennart Schneider, Julia Moosbauer, Martin Binder, Bernd Bischl:
YAHPO Gym - An Efficient Multi-Objective Multi-Fidelity Benchmark for Hyperparameter Optimization. AutoML 2022: 3/1-39 - [i7]Julia Moosbauer, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl:
Enhancing Explainability of Hyperparameter Optimization via Bayesian Algorithm Execution. CoRR abs/2206.05447 (2022) - [i6]Florian Karl, Tobias Pielok, Julia Moosbauer, Florian Pfisterer, Stefan Coors, Martin Binder, Lennart Schneider, Janek Thomas, Jakob Richter, Michel Lang, Eduardo C. Garrido-Merchán, Jürgen Branke, Bernd Bischl:
Multi-Objective Hyperparameter Optimization - An Overview. CoRR abs/2206.07438 (2022) - 2021
- [c2]Julia Moosbauer, Julia Herbinger, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl:
Explaining Hyperparameter Optimization via Partial Dependence Plots. NeurIPS 2021: 2280-2291 - [i5]Florian Pfisterer, Lennart Schneider, Julia Moosbauer, Martin Binder, Bernd Bischl:
YAHPO Gym - Design Criteria and a new Multifidelity Benchmark for Hyperparameter Optimization. CoRR abs/2109.03670 (2021) - [i4]Julia Moosbauer, Julia Herbinger, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl:
Explaining Hyperparameter Optimization via Partial Dependence Plots. CoRR abs/2111.04820 (2021) - [i3]Julia Moosbauer, Martin Binder, Lennart Schneider, Florian Pfisterer, Marc Becker, Michel Lang, Lars Kotthoff, Bernd Bischl:
Automated Benchmark-Driven Design and Explanation of Hyperparameter Optimizers. CoRR abs/2111.14756 (2021) - 2020
- [c1]Martin Binder, Julia Moosbauer, Janek Thomas, Bernd Bischl:
Multi-objective hyperparameter tuning and feature selection using filter ensembles. GECCO 2020: 471-479 - [i2]Abhijeet Parida, Aadhithya Sankar, Rami Eisawy, Tom Finck, Benedikt Wiestler, Franz Pfister, Julia Moosbauer:
Train, Learn, Expand, Repeat. CoRR abs/2003.08469 (2020)
2010 – 2019
- 2019
- [i1]Martin Binder, Julia Moosbauer, Janek Thomas, Bernd Bischl:
Model-Agnostic Approaches to Multi-Objective Simultaneous Hyperparameter Tuning and Feature Selection. CoRR abs/1912.12912 (2019)
Coauthor Index
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