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Bernd Bischl

Department of Statistics, Ludwig-Maximilians-Universit├Ąt M├╝nchen, Germany

Accelerated Componentwise Gradient Boosting using Efficient Data Representation and Momentum-based Optimization

Oct 07, 2021
Daniel Schalk, Bernd Bischl, David R├╝gamer

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Deep Variational Clustering Framework for Self-labeling of Large-scale Medical Images

Sep 22, 2021
Farzin Soleymani, Mohammad Eslami, Tobias Elze, Bernd Bischl, Mina Rezaei

* arXiv admin note: text overlap with arXiv:2109.05232 

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Deep Bregman Divergence for Contrastive Learning of Visual Representations

Sep 15, 2021
Mina Rezaei, Farzin Soleymani, Bernd Bischl, Shekoofeh Azizi

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Automatic Componentwise Boosting: An Interpretable AutoML System

Sep 12, 2021
Stefan Coors, Daniel Schalk, Bernd Bischl, David R├╝gamer

* 6 pages, 4 figures, ECML-PKDD Workshop on Automating Data Science 2021 

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Learning Statistical Representation with Joint Deep Embedded Clustering

Sep 11, 2021
Mina Rezaei, Emilio Dorigatti, David Ruegamer, Bernd Bischl

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YAHPO Gym -- Design Criteria and a new Multifidelity Benchmark for Hyperparameter Optimization

Sep 08, 2021
Florian Pfisterer, Lennart Schneider, Julia Moosbauer, Martin Binder, Bernd Bischl

* Preprint. Under review. 17 pages, 4 tables, 5 figures 

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Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process

Sep 03, 2021
Christoph Molnar, Timo Freiesleben, Gunnar K├Ânig, Giuseppe Casalicchio, Marvin N. Wright, Bernd Bischl

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Developing Open Source Educational Resources for Machine Learning and Data Science

Aug 10, 2021
Ludwig Bothmann, Sven Strickroth, Giuseppe Casalicchio, David R├╝gamer, Marius Lindauer, Fabian Scheipl, Bernd Bischl

* 6 pages 

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Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges

Jul 14, 2021
Bernd Bischl, Martin Binder, Michel Lang, Tobias Pielok, Jakob Richter, Stefan Coors, Janek Thomas, Theresa Ullmann, Marc Becker, Anne-Laure Boulesteix, Difan Deng, Marius Lindauer

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Mutation is all you need

Jul 04, 2021
Lennart Schneider, Florian Pfisterer, Martin Binder, Bernd Bischl

* Accepted for the 8th ICML Workshop on Automated Machine Learning (2021). 10 pages, 1 table, 3 figures 

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Decomposition of Global Feature Importance into Direct and Associative Components (DEDACT)

Jun 15, 2021
Gunnar K├Ânig, Timo Freiesleben, Bernd Bischl, Giuseppe Casalicchio, Moritz Grosse-Wentrup

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Meta-Learning for Symbolic Hyperparameter Defaults

Jun 11, 2021
Pieter Gijsbers, Florian Pfisterer, Jan N. van Rijn, Bernd Bischl, Joaquin Vanschoren

* Pieter Gijsbers and Florian Pfisterer contributed equally to the paper. V1: Two page GECCO poster paper accepted at GECCO 2021. V2: The original full length paper (8 pages) with appendix 

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Grouped Feature Importance and Combined Features Effect Plot

Apr 23, 2021
Quay Au, Julia Herbinger, Clemens Stachl, Bernd Bischl, Giuseppe Casalicchio

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deepregression: a Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression

Apr 06, 2021
David R├╝gamer, Ruolin Shen, Christina Bukas, Lisa Barros de Andrade e Sousa, Dominik Thalmeier, Nadja Klein, Chris Kolb, Florian Pfisterer, Philipp Kopper, Bernd Bischl, Christian L. M├╝ller

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Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features

Apr 01, 2021
Florian Pargent, Florian Pfisterer, Janek Thomas, Bernd Bischl

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Deep Semi-Supervised Learning for Time Series Classification

Feb 06, 2021
Jann Goschenhofer, Rasmus Hvingelby, David R├╝gamer, Janek Thomas, Moritz Wagner, Bernd Bischl

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Semi-Structured Deep Piecewise Exponential Models

Nov 11, 2020
Philipp Kopper, Sebastian P├Âlsterl, Christian Wachinger, Bernd Bischl, Andreas Bender, David R├╝gamer

* 8 pages, 3 figures 

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Debiasing classifiers: is reality at variance with expectation?

Nov 04, 2020
Ashrya Agrawal, Florian Pfisterer, Bernd Bischl, Jiahao Chen, Srijan Sood, Sameena Shah, Francois Buet-Golfouse, Bilal A Mateen, Sebastian Vollmer

* 11 pages, under review 

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Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges

Oct 19, 2020
Christoph Molnar, Giuseppe Casalicchio, Bernd Bischl

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Neural Mixture Distributional Regression

Oct 14, 2020
David R├╝gamer, Florian Pfisterer, Bernd Bischl

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Symplectic Gaussian Process Regression of Hamiltonian Flow Maps

Sep 11, 2020
Katharina Rath, Christopher G. Albert, Bernd Bischl, Udo von Toussaint

* 24 pages, 9 figures 

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mlr3proba: Machine Learning Survival Analysis in R

Aug 18, 2020
Raphael Sonabend, Franz J. Király, Andreas Bender, Bernd Bischl, Michel Lang

* Submitted to JMLR 

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Relative Feature Importance

Jul 16, 2020
Gunnar K├Ânig, Christoph Molnar, Bernd Bischl, Moritz Grosse-Wentrup

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Pitfalls to Avoid when Interpreting Machine Learning Models

Jul 08, 2020
Christoph Molnar, Gunnar K├Ânig, Julia Herbinger, Timo Freiesleben, Susanne Dandl, Christian A. Scholbeck, Giuseppe Casalicchio, Moritz Grosse-Wentrup, Bernd Bischl

* This article was accepted at the ICML 2020 workshop XXAI: Extending Explainable AI Beyond Deep Models and Classifiers (see

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A General Machine Learning Framework for Survival Analysis

Jun 27, 2020
Andreas Bender, David R├╝gamer, Fabian Scheipl, Bernd Bischl

* Accepted at ECML PKDD 2020, Research Track 

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Model-agnostic Feature Importance and Effects with Dependent Features -- A Conditional Subgroup Approach

Jun 08, 2020
Christoph Molnar, Gunnar K├Ânig, Bernd Bischl, Giuseppe Casalicchio

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Multi-Objective Counterfactual Explanations

Apr 23, 2020
Susanne Dandl, Christoph Molnar, Martin Binder, Bernd Bischl

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