| Dbest: Revisiting approximate query processing engines with machine learning models Q Ma, P Triantafillou Proceedings of the 2019 International Conference on Management of Data, 1553 …, 2019 | 83 | 2019 |
| Learned approximate query processing: Make it light, accurate and fast Q Ma, AM Shanghooshabad, M Almasi, M Kurmanji, P Triantafillou Conference on Innovative Data Systems,(CIDR21), 2021 | 26 | 2021 |
| Pgmjoins: Random join sampling with graphical models AM Shanghooshabad, M Kurmanji, Q Ma, M Shekelyan, M Almasi, ... Proceedings of the 2021 International Conference on Management of Data, 1610 …, 2021 | 19 | 2021 |
| Weighted random sampling over joins M Shekelyan, G Cormode, P Triantafillou, A Shanghooshabad, Q Ma arXiv preprint arXiv:2201.02670, 2022 | 7 | 2022 |
| Query-centric regression for in-dbms analytics Q Ma, P Triantafillou Proceedings of the 22nd International Workshop on Design, Optimization …, 2020 | 2 | 2020 |
| Query-centric regression Q Ma, P Triantafillou Information Systems 104, 101736, 2022 | 1 | 2022 |
| SieveJoin: Boosting Multi-Way Joins with Reusable Bloom Filters Q Ma arXiv preprint arXiv:2308.16370, 2023 | | 2023 |
| Streaming weighted sampling over join queries M Shekelyan, G Cormode, Q Ma, AM Shanghooshabad, P Triantafillou Proceedings of the 26th International Conference on Extending Database …, 2023 | | 2023 |
| Approximate query processing using machine learning Q Ma University of Warwick, 2021 | | 2021 |
Peter TriantafillouProfessor, Computer Science, University of WarwickVerified email at warwick.ac.uk
