Julia Moosbauer

17 papers A* 2A 1Journal 12Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	Position: A Call to Action for a Human-Centered AutoML Paradigm. ICML Marius Lindauer, Florian Karl, Anne Klier, Julia Moosbauer, Alexander Tornede, Andreas Müller, Frank Hutter, Matthias Feurer, Bernd Bischl
2024	J	`jnl`	Position: A Call to Action for a Human-Centered AutoML Paradigm. CoRR Marius Lindauer, Florian Karl, Anne Klier, Julia Moosbauer, Alexander Tornede, Andreas Müller, Frank Hutter, Matthias Feurer, Bernd Bischl
2023	J	`jnl`	Multi-Objective Hyperparameter Optimization in Machine Learning - An Overview. ACM Trans. Evol. Learn. Optim. 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
2023	J	`jnl`	Position Paper: Bridging the Gap Between Machine Learning and Sensitivity Analysis. CoRR Christian A. Scholbeck, Julia Moosbauer, Giuseppe Casalicchio, Hoshin Gupta, Bernd Bischl, Christian Heumann
2023	J	`jnl`	RAISE - Radiology AI Safety, an End-to-end lifecycle approach. CoRR 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
2023	—	`—`	Towards explainable automated machine learning. Julia Moosbauer
2022	J	`jnl`	Automated Benchmark-Driven Design and Explanation of Hyperparameter Optimizers. IEEE Trans. Evol. Comput. Julia Moosbauer, Martin Binder, Lennart Schneider, Florian Pfisterer, Marc Becker, Michel Lang, Lars Kotthoff, Bernd Bischl
2022	J	`jnl`	Enhancing Explainability of Hyperparameter Optimization via Bayesian Algorithm Execution. CoRR Julia Moosbauer, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl
2022	J	`jnl`	Multi-Objective Hyperparameter Optimization - An Overview. CoRR 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
2022	—	`conf`	YAHPO Gym - An Efficient Multi-Objective Multi-Fidelity Benchmark for Hyperparameter Optimization. AutoML Florian Pfisterer, Lennart Schneider, Julia Moosbauer, Martin Binder, Bernd Bischl
2021	J	`jnl`	Automated Benchmark-Driven Design and Explanation of Hyperparameter Optimizers. CoRR Julia Moosbauer, Martin Binder, Lennart Schneider, Florian Pfisterer, Marc Becker, Michel Lang, Lars Kotthoff, Bernd Bischl
2021	A*	`conf`	Explaining Hyperparameter Optimization via Partial Dependence Plots. NeurIPS Julia Moosbauer, Julia Herbinger, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl
2021	J	`jnl`	Explaining Hyperparameter Optimization via Partial Dependence Plots. CoRR Julia Moosbauer, Julia Herbinger, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl
2021	J	`jnl`	YAHPO Gym - Design Criteria and a new Multifidelity Benchmark for Hyperparameter Optimization. CoRR Florian Pfisterer, Lennart Schneider, Julia Moosbauer, Martin Binder, Bernd Bischl
2020	A	`conf`	Multi-objective hyperparameter tuning and feature selection using filter ensembles. GECCO Martin Binder, Julia Moosbauer, Janek Thomas, Bernd Bischl
2020	J	`jnl`	Train, Learn, Expand, Repeat. CoRR Abhijeet Parida, Aadhithya Sankar, Rami Eisawy, Tom Finck, Benedikt Wiestler, Franz Pfister, Julia Moosbauer
2019	J	`jnl`	Model-Agnostic Approaches to Multi-Objective Simultaneous Hyperparameter Tuning and Feature Selection. CoRR Martin Binder, Julia Moosbauer, Janek Thomas, Bernd Bischl