| Scalable and robust set similarity join T Christiani, R Pagh, J Sivertsen 2018 IEEE 34th international conference on data engineering (ICDE), 1240-1243, 2018 | 39 | 2018 |
| Approximate furthest neighbor in high dimensions R Pagh, F Silvestri, J Sivertsen, M Skala Similarity Search and Applications: 8th International Conference, SISAP 2015 …, 2015 | 34 | 2015 |
| Distance sensitive bloom filters without false negatives M Goswami, R Pagh, F Silvestri, J Sivertsen Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete …, 2017 | 25 | 2017 |
| Approximate furthest neighbor with application to annulus query R Pagh, F Silvestri, J Sivertsen, M Skala Information Systems 64, 152-162, 2017 | 15 | 2017 |
| Scalable learning through linearithmic time kernel approximation techniques J von Tangen Sivertsen Master’s thesis, IT University of Copenhagen, 2014 | 3 | 2014 |
| The space complexity of inner product filters R Pagh, J Sivertsen arXiv preprint arXiv:1909.10766, 2019 | 2 | 2019 |
| Similarity Problems in High Dimensions JT Sivertsen arXiv preprint arXiv:1906.04842, 2019 | 1 | 2019 |
| Fast nearest neighbor preserving embeddings J Sivertsen arXiv preprint arXiv:1707.06867, 2017 | 1 | 2017 |
| ITU DS.: Similarity Problems in High Dimensions. D-2018-140 J Sivertsen | | 2018 |
| Distance Sensitive Bloom Filters M Goswami, R Pagh, F Silvestri, J Sivertsen | | 2016 |
| Library software FN R Pagh, F Silvestri, J Sivertsen, M Skala | | 2015 |
Rasmus PaghProfessor of computer science, University of Copenhagen在 di.ku.dk 的电子邮件经过验证
