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Lennart Schneider
Lennart Schneider
PhD Student, LMU Munich
Verified email at stat.uni-muenchen.de - Homepage
Title
Cited by
Cited by
Year
mirt: Multidimensional item response theory
P Chalmers, J Pritikin, A Robitzsch, M Zoltak, K Kim, CF Falk, A Meade, ...
R package version 1 (1), 2020
66*2020
nonnest2: Tests of non-nested models
E Merkle, D You, L Schneider, S Bae
R Package Version 0.5-5, 2020
432020
YAHPO Gym - An Efficient Multi-Objective Multi-Fidelity Benchmark for Hyperparameter Optimization
F Pfisterer*, L Schneider*, J Moosbauer, M Binder, B Bischl
First Conference on Automated Machine Learning (Main Track), 2022
392022
Multi-Objective Hyperparameter Optimization in Machine Learning – An Overview
F Karl, T Pielok, J Moosbauer, F Pfisterer, S Coors, M Binder, L Schneider, ...
ACM Transactions on Evolutionary Learning, 2023
31*2023
Model Selection of Nested and Non-Nested Item Response Models using Vuong Tests
L Schneider, RP Chalmers, R Debelak, EC Merkle
Multivariate Behavioral Research, 1-21, 2019
302019
mlr3pipelines - Flexible Machine Learning Pipelines in R
M Binder, F Pfisterer, M Lang, L Schneider, L Kotthoff, B Bischl
J. Mach. Learn. Res. 22, 184:1-184:7, 2021
272021
An R toolbox for score-based measurement invariance tests in IRT models
L Schneider, C Strobl, A Zeileis, R Debelak
Behavior Research Methods, 1-13, 2021
222021
A computational reproducibility study of PLOS ONE articles featuring longitudinal data analyses
H Seibold, S Czerny, S Decke, R Dieterle, T Eder, S Fohr, N Hahn, ...
Plos one 16 (6), e0251194, 2021
202021
HPO X ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis
L Schneider*, L Schäpermeier*, RP Prager*, B Bischl, H Trautmann, ...
International Conference on Parallel Problem Solving from Nature, 575-589, 2022
112022
Automated benchmark-driven design and explanation of hyperparameter optimizers
J Moosbauer, M Binder, L Schneider, F Pfisterer, M Becker, M Lang, ...
IEEE Transactions on Evolutionary Computation 26 (6), 1336-1350, 2022
92022
Mutation is all you need
L Schneider, F Pfisterer, M Binder, B Bischl
8th ICML Workshop on Automated Machine Learning, 2021
82021
mlr3: Machine learning in R—Next generation
M Lang, B Bischl, J Richter, P Schratz, G Casalicchio, S Coors, Q Au, ...
72020
Using the raschtree function for detecting differential item functioning in the Rasch model
C Strobl, L Schneider, J Kopf, A Zeileis
52021
psychotools: Infrastructure for psychometric modeling [Computer software manual]
A Zeileis, C Strobl, F Wickelmaier, B Komboz, J Kopf, L Schneider, ...
R package version 0.5–1). Retrieved from https://CRAN. R‐project. org …, 2020
52020
A collection of quality diversity optimization problems derived from hyperparameter optimization of machine learning models
L Schneider, F Pfisterer, J Thomas, B Bischl
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2022
32022
Correction: A computational reproducibility study of PLOS ONE articles featuring longitudinal data analyses
H Seibold, S Czerny, S Decke, R Dieterle, T Eder, S Fohr, N Hahn, ...
Plos one 17 (5), e0269047, 2022
32022
Tackling Neural Architecture Search With Quality Diversity Optimization
L Schneider, F Pfisterer, P Kent, J Branke, B Bischl, J Thomas
First Conference on Automated Machine Learning (Main Track), 2022
32022
Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features
RP Prager, K Dietrich, L Schneider, L Schäpermeier, B Bischl, P Kerschke, ...
Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic …, 2023
22023
Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models
L Schneider, B Bischl, J Thomas
Proceedings of the Genetic and Evolutionary Computation Conference, 538-547, 2023
22023
Advanced Tuning Methods and Black Box Optimization
L Schneider, M Becker
Applied Machine Learning Using mlr3 in R, 116-145, 2023
12023
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Articles 1–20