| 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 | 940 | 2016 |
| 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 | 421 | 2023 |
| 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 | 402 | 2019 |
| 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 | 314 | 2019 |
| 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 | 196 | 2017 |
| 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 | 55 | 2018 |
| 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, ... | 36 | 2019 |
| 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 | 29 | 2017 |
| 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 | 26 | 2017 |
| 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 | 24 | 2022 |
| 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 and Optimization 3 (4), 1-50, 2023 | 21 | 2023 |
| 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 | 20 | 2016 |
| 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 | 18 | 2016 |
| 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 | 16 | 2017 |
| mlr3 book M Becker, M Binder, B Bischl, N Foss, L Kotthoff, M Lan, F Pfisterer, ... URl: https://mlr3book. mlr-org. com 28, 29-30, 2021 | 13 | 2021 |
| Improving adaptive seamless designs through Bayesian optimization J Richter, T Friede, J Rahnenführer Biometrical Journal 64 (5), 948-963, 2022 | 10 | 2022 |
| 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 | 9 | 2021 |
| 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 | 9 | 2017 |
| mlr Tutorial J Schiffner, B Bischl, M Lang, J Richter, ZM Jones, P Probst, F Pfisterer, ... arXiv preprint arXiv:1609.06146, 2016 | 9 | 2016 |
| 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 | 8 | 2020 |
Michel LangTU Dortmund; LMU MunichΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα statistik.tu-dortmund.de
