| Implicit parallelism through deep language embedding A Alexandrov, A Kunft, A Katsifodimos, F Schüler, L Thamsen, O Kao, ... Proceedings of the 2015 ACM SIGMOD International Conference on Management of …, 2015 | 90 | 2015 |
| An Intermediate Representation for Optimizing Machine Learning Pipelines A Kunft, A Katsifodimos, S Schelter, S Breß, T Rabl, V Markl Proceedings of the VLDB Endowment 12 (11), 1553-1567, 2019 | 64 | 2019 |
| Bridging the gap: towards optimization across linear and relational algebra A Kunft, A Alexandrov, A Katsifodimos, V Markl Proceedings of the 3rd ACM SIGMOD Workshop on Algorithms and Systems for …, 2016 | 46 | 2016 |
| Blockjoin: Efficient matrix partitioning through joins A Kunft, A Katsifodimos, S Schelter, T Rabl, V Markl VLDB 2017: 43rd International Conference on Very Large Data Bases, 2061-2072, 2017 | 27 | 2017 |
| PEEL: A framework for benchmarking distributed systems and algorithms C Boden, A Alexandrov, A Kunft, T Rabl, V Markl Performance Evaluation and Benchmarking for the Analytics Era: 9th TPC …, 2018 | 17 | 2018 |
| Scootr: Scaling r dataframes on dataflow systems A Kunft, L Stadler, D Bonetta, C Basca, J Meiners, S Breß, T Rabl, ... Proceedings of the ACM Symposium on Cloud Computing, 288-300, 2018 | 14 | 2018 |
| Optimizing end-to-end machine learning pipelines for model training A Kunft PQDT-Global, 2019 | 1 | 2019 |
