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Works (7)

Multi-Objective Hyperparameter Optimization in Machine Learning—An Overview

ACM Transactions on Evolutionary Learning and Optimization
2023-12-31 | Journal article
DOI: 10.1145/3610536
Contributors: Florian Karl; Tobias Pielok; Julia Moosbauer; Florian Pfisterer; Stefan Coors; Martin Binder; Lennart Schneider; Janek Thomas; Jakob Richter; Michel Lang et al.
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Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features

2023-08-30 | Conference paper
DOI: 10.1145/3594805.3607136
Contributors: Raphael Patrick Prager; Konstantin Dietrich; Lennart Schneider; Lennart Schäpermeier; Bernd Bischl; Pascal Kerschke; Heike Trautmann; Olaf Mersmann
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Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models

2023-07-15 | Conference paper
DOI: 10.1145/3583131.3590380
Contributors: Lennart Schneider; Bernd Bischl; Janek Thomas
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HPO $$\times $$ ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis

2022 | Book chapter
DOI: 10.1007/978-3-031-14714-2_40
Contributors: Lennart Schneider; Lennart Schäpermeier; Raphael Patrick Prager; Bernd Bischl; Heike Trautmann; Pascal Kerschke
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Automated Benchmark-Driven Design and Explanation of Hyperparameter Optimizers

IEEE Transactions on Evolutionary Computation
2022-12 | Journal article
DOI: 10.1109/TEVC.2022.3211336
Contributors: Julia Moosbauer; Martin Binder; Lennart Schneider; Florian Pfisterer; Marc Becker; Michel Lang; Lars Kotthoff; Bernd Bischl
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An R toolbox for score-based measurement invariance tests in IRT models

Behavior Research Methods
2021-12-16 | Journal article
DOI: 10.3758/s13428-021-01689-0
Contributors: Lennart Schneider; Carolin Strobl; Achim Zeileis; Rudolf Debelak
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Model Selection of Nested and Non-Nested Item Response Models Using Vuong Tests

Multivariate Behavioral Research
2020-09-02 | Journal article
DOI: 10.1080/00273171.2019.1664280
Contributors: Lennart Schneider; R. Philip Chalmers; Rudolf Debelak; Edgar C. Merkle
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