Florian Pfisterer

45 papers B 1Journal 32Unranked 11

Year	Rank	Type	Title / Venue / Authors
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	—	`conf`	One Model Many Scores: Using Multiverse Analysis to Prevent Fairness Hacking and Evaluate the Influence of Model Design Decisions. FAccT Jan Simson, Florian Pfisterer, Christoph Kern
2023	J	`jnl`	A geometric framework for outlier detection in high-dimensional data. WIREs Data. Mining. Knowl. Discov. Moritz Herrmann, Florian Pfisterer, Fabian Scheipl
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	J	`jnl`	Everything, Everywhere All in One Evaluation: Using Multiverse Analysis to Evaluate the Influence of Model Design Decisions on Algorithmic Fairness. CoRR Jan Simson, Florian Pfisterer, Christoph Kern
2023	J	`jnl`	Fairness Audits and Debiasing Using \pkg{mlr3fairness}. R J. Florian Pfisterer, Siyi Wei, Sebastian J. Vollmer, Michel Lang, Bernd Bischl
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	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	—	`conf`	Using Multiverse Analysis to Evaluate the Influence of Model Design Decisions on Algorithmic Fairness. HHAI Jan Simson, Florian Pfisterer, Christoph Kern
2023	—	`conf`	What If? Using Multiverse Analysis to Evaluate the Influence of Model Design Decisions on Algorithmic Fairness. EWAF Jan Simson, Florian Pfisterer, Christoph Kern
2023	J	`jnl`	deepregression: A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression. J. Stat. Softw. David Rügamer, Chris Kolb, Cornelius Fritz, Florian Pfisterer, Philipp Kopper, Bernd Bischl, Ruolin Shen, Christina Bukas, Lisa Barros de Andrade e Sousa, Dominik Thalmeier, Philipp F. M. Baumann, Lucas Kook, Nadja Klein, Christian L. Müller
2022	J	`jnl`	A Collection of Quality Diversity Optimization Problems Derived from Hyperparameter Optimization of Machine Learning Models. CoRR Lennart Schneider, Florian Pfisterer, Janek Thomas, Bernd Bischl
2022	—	`conf`	A collection of quality diversity optimization problems derived from hyperparameter optimization of machine learning models. GECCO Companion Lennart Schneider, Florian Pfisterer, Janek Thomas, Bernd Bischl
2022	J	`jnl`	A geometric framework for outlier detection in high-dimensional data. CoRR Moritz Herrmann, Florian Pfisterer, Fabian Scheipl
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	—	`—`	Democratizing machine learning: contributions in AutoML and fairness. Florian Pfisterer
2022	—	`conf`	Evaluating Domain Generalization for Survival Analysis in Clinical Studies. CHIL Florian Pfisterer, Chris Harbron, Gunther Jansen, Tao Xu
2022	J	`jnl`	Flexible Group Fairness Metrics for Survival Analysis. CoRR Raphael Sonabend, Florian Pfisterer, Alan Mishler, Moritz Schauer, Lukas Burk, Sebastian J. Vollmer
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`	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`	Multi-objective counterfactual fairness. GECCO Companion Susanne Dandl, Florian Pfisterer, Bernd Bischl
2022	J	`jnl`	Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features. Comput. Stat. Florian Pargent, Florian Pfisterer, Janek Thomas, Bernd Bischl
2022	—	`conf`	Tackling Neural Architecture Search With Quality Diversity Optimization. AutoML Lennart Schneider, Florian Pfisterer, Paul Kent, Jürgen Branke, Bernd Bischl, Janek Thomas
2022	J	`jnl`	Tackling Neural Architecture Search With Quality Diversity Optimization. CoRR Lennart Schneider, Florian Pfisterer, Paul Kent, Jürgen Branke, Bernd Bischl, Janek Thomas
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	—	`conf`	Learning multiple defaults for machine learning algorithms. GECCO Companion Florian Pfisterer, Jan N. van Rijn, Philipp Probst, Andreas C. Müller, Bernd Bischl
2021	J	`jnl`	Meta-Learning for Symbolic Hyperparameter Defaults. CoRR Pieter Gijsbers, Florian Pfisterer, Jan N. van Rijn, Bernd Bischl, Joaquin Vanschoren
2021	—	`conf`	Meta-learning for symbolic hyperparameter defaults. GECCO Companion Pieter Gijsbers, Florian Pfisterer, Jan N. van Rijn, Bernd Bischl, Joaquin Vanschoren
2021	J	`jnl`	Mutation is all you need. CoRR Lennart Schneider, Florian Pfisterer, Martin Binder, Bernd Bischl
2021	J	`jnl`	Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features. CoRR Florian Pargent, Florian Pfisterer, Janek Thomas, 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
2021	J	`jnl`	deepregression: a Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression. CoRR David Rügamer, Ruolin Shen, Christina Bukas, Lisa Barros de Andrade e Sousa, Dominik Thalmeier, Nadja Klein, Chris Kolb, Florian Pfisterer, Philipp Kopper, Bernd Bischl, Christian L. Müller
2021	J	`jnl`	mcboost: Multi-Calibration Boosting for R. J. Open Source Softw. Florian Pfisterer, Christoph Kern, Susanne Dandl, Matthew Sun, Michael P. Kim, Bernd Bischl
2021	J	`jnl`	mlr3pipelines - Flexible Machine Learning Pipelines in R. J. Mach. Learn. Res. Martin Binder, Florian Pfisterer, Michel Lang, Lennart Schneider, Lars Kotthoff, Bernd Bischl
2020	J	`jnl`	Debiasing classifiers: is reality at variance with expectation? CoRR Ashrya Agrawal, Florian Pfisterer, Bernd Bischl, Jiahao Chen, Srijan Sood, Sameena Shah, Francois Buet-Golfouse, Bilal A. Mateen, Sebastian J. Vollmer
2020	J	`jnl`	Neural Mixture Distributional Regression. CoRR David Rügamer, Florian Pfisterer, Bernd Bischl
2019	J	`jnl`	Benchmarking time series classification - Functional data vs machine learning approaches. CoRR Florian Pfisterer, Laura Beggel, Xudong Sun, Fabian Scheipl, Bernd Bischl
2019	—	`conf`	High Dimensional Restrictive Federated Model Selection with Multi-objective Bayesian Optimization over Shifted Distributions. IntelliSys (1) Xudong Sun, Andrea Bommert, Florian Pfisterer, Jörg Rahnenführer, Michel Lang, Bernd Bischl
2019	J	`jnl`	High Dimensional Restrictive Federated Model Selection with multi-objective Bayesian Optimization over shifted distributions. CoRR Xudong Sun, Andrea Bommert, Florian Pfisterer, Jörg Rahnenführer, Michel Lang, Bernd Bischl
2019	J	`jnl`	Multi-Objective Automatic Machine Learning with AutoxgboostMC. CoRR Florian Pfisterer, Stefan Coors, Janek Thomas, Bernd Bischl
2019	J	`jnl`	Towards Human Centered AutoML. CoRR Florian Pfisterer, Janek Thomas, Bernd Bischl
2019	J	`jnl`	mlr3: A modern object-oriented machine learning framework in R. J. Open Source Softw. Michel Lang, Martin Binder, Jakob Richter, Patrick Schratz, Florian Pfisterer, Stefan Coors, Quay Au, Giuseppe Casalicchio, Lars Kotthoff, Bernd Bischl
2018	J	`jnl`	Learning Multiple Defaults for Machine Learning Algorithms. CoRR Florian Pfisterer, Jan N. van Rijn, Philipp Probst, Andreas C. Müller, Bernd Bischl
2016	J	`jnl`	mlr Tutorial. CoRR Julia Schiffner, Bernd Bischl, Michel Lang, Jakob Richter, Zachary M. Jones, Philipp Probst, Florian Pfisterer, Mason Gallo, Dominik Kirchhoff, Tobias Kühn, Janek Thomas, Lars Kotthoff