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Jakob Richter
Jakob Richter
Bestätigte E-Mail-Adresse bei statistik.tu-dortmund.de - Startseite
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Zitiert von
Zitiert von
Jahr
mlr: Machine Learning in R
B Bischl, M Lang, L Kotthoff, J Schiffner, J Richter, E Studerus, ...
The Journal of Machine Learning Research 17 (1), 5938-5942, 2016
7392016
Hyperparameter tuning and performance assessment of statistical and machine-learning algorithms using spatial data
P Schratz, J Muenchow, E Iturritxa, J Richter, A Brenning
Ecological Modelling 406, 109-120, 2019
1772019
mlrMBO: A modular framework for model-based optimization of expensive black-box functions
B Bischl, J Richter, J Bossek, D Horn, J Thomas, M Lang
arXiv preprint arXiv:1703.03373, 2017
1602017
mlr3: A modern object-oriented machine learning framework in R
M Lang, M Binder, J Richter, P Schratz, F Pfisterer, S Coors, Q Au, ...
Journal of Open Source Software 4 (44), 1903, 2019
1262019
Hyperparameter optimization: Foundations, algorithms, best practices and open challenges
B Bischl, M Binder, M Lang, T Pielok, J Richter, S Coors, J Thomas, ...
arXiv preprint arXiv:2107.05847, 2021
462021
Performance evaluation and hyperparameter tuning of statistical and machine-learning models using spatial data
P Schratz, J Muenchow, E Iturritxa, J Richter, A Brenning
arXiv preprint arXiv:1803.11266, 2018
392018
BBmisc: Miscellaneous Helper Functions for B
B Bischl, M Lang, J Bossek, D Horn, J Richter, D Surmann
Bischl. R package version 1, 2017, 2017
202017
Machine learning in R
B Bischl, M Lang, L Kotthoff, J Schiffner, J Richter, E Studerus, ...
J. Mach. Learn. Res. 17, 5938-5942, 2016
192016
BBmisc: Miscellaneous helper functions for B. Bischl
B Bischl, M Lang, J Bossek, D Horn, J Richter, D Surmann
R package version 1.11, 2017
182017
mlr3: A modern object-oriented machine learning framework in RJ Open Source Softw
M Lang, M Binder, J Richter, P Schratz, F Pfisterer, S Coors, Q Au, ...
172019
mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions, 2017
B Bischl, J Richter, J Bossek, D Horn, J Thomas, M Lang
URL http://arxiv. org/abs/1703 3373, 3, 2016
162016
Faster model-based optimization through resource-aware scheduling strategies
J Richter, H Kotthaus, B Bischl, P Marwedel, J Rahnenführer, M Lang
International conference on learning and intelligent optimization, 267-273, 2016
132016
Rambo: Resource-aware model-based optimization with scheduling for heterogeneous runtimes and a comparison with asynchronous model-based optimization
H Kotthaus, J Richter, A Lang, J Thomas, B Bischl, P Marwedel, ...
International conference on learning and intelligent optimization, 180-195, 2017
112017
mlr Tutorial
J Schiffner, B Bischl, M Lang, J Richter, ZM Jones, P Probst, F Pfisterer, ...
arXiv preprint arXiv:1609.06146, 2016
82016
ParamHelpers: Helpers for parameters in black-box optimization, tuning and machine learning
B Bischl, M Lang, J Bossek, D Horn, K Schork, J Richter, P Kerschke
R package version 1, 23, 2016
72016
Model-based optimization with concept drifts
J Richter, J Shi, JJ Chen, J Rahnenführer, M Lang
Proceedings of the 2020 genetic and evolutionary computation conference, 877-885, 2020
62020
Model-based optimization of subgroup weights for survival analysis
J Richter, K Madjar, J Rahnenführer
Bioinformatics 35 (14), i484-i491, 2019
62019
mlr3 book
M Becker, M Binder, B Bischl, M Lang, F Pfisterer, NG Reich, J Richter, ...
URl: https://mlr3book. mlr-org. com, 2020
52020
MODES: model-based optimization on distributed embedded systems
J Shi, J Bian, J Richter, KH Chen, J Rahnenführer, H Xiong, JJ Chen
Machine Learning 110 (6), 1527-1547, 2021
42021
Improving adaptive seamless designs through Bayesian optimization
J Richter, T Friede, J Rahnenführer
Biometrical Journal 64 (5), 948-963, 2022
32022
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