Casalicchio, Giuseppe

11 publications

ICLR 2025 Efficient and Accurate Explanation Estimation with Distribution Compression Hubert Baniecki, Giuseppe Casalicchio, Bernd Bischl, Przemyslaw Biecek

ECML-PKDD 2025 Explaining Bayesian Optimization by Shapley Values Facilitates Human-AI Collaboration for Exosuit Personalization Julian Rodemann, Federico Croppi, Philipp Arens, Yusuf Sale, Julia Herbinger, Bernd Bischl, Eyke Hüllermeier, Thomas Augustin, Conor J. Walsh, Giuseppe Casalicchio

JMLR 2024 Decomposing Global Feature Effects Based on Feature Interactions Julia Herbinger, Marvin N. Wright, Thomas Nagler, Bernd Bischl, Giuseppe Casalicchio

ECML-PKDD 2024 On the Robustness of Global Feature Effect Explanations Hubert Baniecki, Giuseppe Casalicchio, Bernd Bischl, Przemyslaw Biecek

ICML 2024 Position: Why We Must Rethink Empirical Research in Machine Learning Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger, Giuseppe Casalicchio, Marcel Wever, Matthias Feurer, David Rügamer, Eyke Hüllermeier, Anne-Laure Boulesteix, Bernd Bischl

ECML-PKDD 2023 Interpretable Regional Descriptors: Hyperbox-Based Local Explanations Susanne Dandl, Giuseppe Casalicchio, Bernd Bischl, Ludwig Bothmann

AISTATS 2022 REPID: Regional Effect Plots with Implicit Interaction Detection Julia Herbinger, Bernd Bischl, Giuseppe Casalicchio

NeurIPS 2021 Explaining Hyperparameter Optimization via Partial Dependence Plots Julia Moosbauer, Julia Herbinger, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl

ICMLW 2021 Towards Explaining Hyperparameter Optimization via Partial Dependence Plots Julia Moosbauer, Julia Herbinger, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl

ECML-PKDD 2018 Visualizing the Feature Importance for Black Box Models Giuseppe Casalicchio, Christoph Molnar, Bernd Bischl

JMLR 2016 Mlr: Machine Learning in R Bernd Bischl, Michel Lang, Lars Kotthoff, Julia Schiffner, Jakob Richter, Erich Studerus, Giuseppe Casalicchio, Zachary M. Jones