| Learned cardinalities: Estimating correlated joins with deep learning A Kipf, T Kipf, B Radke, V Leis, P Boncz, A Kemper arXiv preprint arXiv:1809.00677, 2018 | 429 | 2018 |
| Query optimization through the looking glass, and what we found running the join order benchmark V Leis, B Radke, A Gubichev, A Mirchev, P Boncz, A Kemper, T Neumann The VLDB Journal 27, 643-668, 2018 | 176 | 2018 |
| Cardinality Estimation Done Right: Index-Based Join Sampling. V Leis, B Radke, A Gubichev, A Kemper, T Neumann Cidr, 2017 | 167 | 2017 |
| Adaptive optimization of very large join queries T Neumann, B Radke Proceedings of the 2018 International Conference on Management of Data, 677-692, 2018 | 76 | 2018 |
| Estimating cardinalities with deep sketches A Kipf, D Vorona, J Müller, T Kipf, B Radke, V Leis, P Boncz, T Neumann, ... Proceedings of the 2019 International Conference on Management of Data, 1937 …, 2019 | 49 | 2019 |
| Concurrent online sampling for all, for free A Birler, B Radke, T Neumann Proceedings of the 16th International Workshop on Data Management on New …, 2020 | 13 | 2020 |
| Learned cardinalities: estimating correlated joins with deep learning (2018) A Kipf, T Kipf, B Radke, V Leis, P Boncz, A Kemper arXiv preprint arXiv:1809.00677, 2019 | 6 | 2019 |
| LinDP++: generalizing linearized DP to crossproducts and non-inner joins B Radke, T Neumann BTW 2019, 57-76, 2019 | 3 | 2019 |
| Estimating Cardinalities with Deep Sketches AKDVJM ThomasKipf, B Radke, VLP Boncz, TNA Kemper | | 2019 |
| Query Optimization: Exercise B Radke | | 2018 |
