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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, ...
Journal of Machine Learning Research 17 (170), 1-5, 2016
8762016
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
3202019
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
2532019
Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges
B Bischl, M Binder, M Lang, T Pielok, J Richter, S Coors, J Thomas, ...
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 13 (2 …, 2023
2452023
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
1862017
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
522018
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, ...
312019
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
252017
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
242017
Multi-Objective Hyperparameter Optimization--An Overview
F Karl, T Pielok, J Moosbauer, F Pfisterer, S Coors, M Binder, L Schneider, ...
arXiv preprint arXiv:2206.07438, 2022
182022
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
182016
Faster model-based optimization through resource-aware scheduling strategies
J Richter, H Kotthaus, B Bischl, P Marwedel, J Rahnenführer, M Lang
Learning and Intelligent Optimization: 10th International Conference, LION …, 2016
182016
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, ...
Learning and Intelligent Optimization: 11th International Conference, LION …, 2017
142017
mlr3book
M Becker, M Binder, B Bischl, N Foss, L Kotthoff, M Lan, F Pfisterer, ...
URl: https://mlr3book. mlr-org. com 28, 29-30, 2021
112021
mlr Tutorial
J Schiffner, B Bischl, M Lang, J Richter, ZM Jones, P Probst, F Pfisterer, ...
arXiv preprint arXiv:1609.06146, 2016
92016
Improving adaptive seamless designs through Bayesian optimization
J Richter, T Friede, J Rahnenführer
Biometrical Journal 64 (5), 948-963, 2022
82022
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
82021
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
82020
Model-based optimization of subgroup weights for survival analysis
J Richter, K Madjar, J Rahnenführer
Bioinformatics 35 (14), i484-i491, 2019
72019
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, 2017
72017
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