| 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 | 261 | 2023 |
| 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 | 24* | 2023 |
| Hyperparameter optimization: Foundations, algorithms, best practices and open challenges. arXiv B Bischl, M Binder, M Lang, T Pielok, J Richter, S Coors, J Thomas, ... arXiv preprint arXiv:2107.05847, 2021 | 7 | 2021 |
| Hyperparameter optimization: foundations, algorithms, best practices, and open challenges. WIREs Data Min Knowl Discov n/a: e1484 B Bischl, M Binder, M Lang, T Pielok, J Richter, S Coors | 5 | 2023 |
| Evolutionary Learning and Optimization J Renzullo, W Weimer, S Forrest, D Yazdani, MN Omidvar, AH Gandomi, ... ACM Transactions on 3 (4), 2023 | | 2023 |
| Approximate Bayesian Inference with Stein Functional Variational Gradient Descent T Pielok, B Bischl, D Rügamer ICLR, 2023 | | 2023 |
| Variable selection using grouped horseshoe priors T Pielok | | 2019 |
