| Learning linear regression models over factorized joins M Schleich, D Olteanu, R Ciucanu Proceedings of the 2016 International Conference on Management of Data, 3-18, 2016 | 198 | 2016 |
| On the tractability of SHAP explanations G Van den Broeck, A Lykov, M Schleich, D Suciu Journal of Artificial Intelligence Research 74, 851-886, 2022 | 161 | 2022 |
| Factorized databases D Olteanu, M Schleich ACM SIGMOD Record 45 (2), 5-16, 2016 | 107 | 2016 |
| In-database learning with sparse tensors M Abo Khamis, HQ Ngo, XL Nguyen, D Olteanu, M Schleich Proceedings of the 37th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of …, 2018 | 77 | 2018 |
| A layered aggregate engine for analytics workloads M Schleich, D Olteanu, M Abo Khamis, HQ Ngo, XL Nguyen Proceedings of the 2019 International Conference on Management of Data, 1642 …, 2019 | 74 | 2019 |
| AC/DC: in-database learning thunderstruck MA Khamis, HQ Ngo, XL Nguyen, D Olteanu, M Schleich Proceedings of the second workshop on data management for end-to-end machine …, 2018 | 64 | 2018 |
| Geco: Quality counterfactual explanations in real time M Schleich, Z Geng, Y Zhang, D Suciu arXiv preprint arXiv:2101.01292, 2021 | 54 | 2021 |
| Functional aggregate queries with additive inequalities MA Khamis, RR Curtin, B Moseley, HQ Ngo, XL Nguyen, D Olteanu, ... ACM Transactions on Database Systems (TODS) 45 (4), 1-41, 2020 | 47 | 2020 |
| Causality-based explanation of classification outcomes L Bertossi, J Li, M Schleich, D Suciu, Z Vagena Proceedings of the Fourth International Workshop on Data Management for End …, 2020 | 40 | 2020 |
| Learning models over relational data using sparse tensors and functional dependencies MA Khamis, HQ Ngo, XL Nguyen, D Olteanu, M Schleich ACM Transactions on Database Systems (TODS) 45 (2), 1-66, 2020 | 33 | 2020 |
| F: Regression models over factorized views D Olteanu, M Schleich Proceedings of the VLDB Endowment 9 (13), 2016 | 33 | 2016 |
| Rk-means: Fast clustering for relational data R Curtin, B Moseley, H Ngo, XL Nguyen, D Olteanu, M Schleich International Conference on Artificial Intelligence and Statistics, 2742-2752, 2020 | 20 | 2020 |
| Multi-layer optimizations for end-to-end data analytics A Shaikhha, M Schleich, A Ghita, D Olteanu Proceedings of the 18th ACM/IEEE International Symposium on Code Generation …, 2020 | 19 | 2020 |
| Learning models over relational data: A brief tutorial M Schleich, D Olteanu, M Abo-Khamis, HQ Ngo, XL Nguyen Scalable Uncertainty Management: 13th International Conference, SUM 2019 …, 2019 | 17 | 2019 |
| Optimizing tensor programs on flexible storage M Schleich, A Shaikhha, D Suciu Proceedings of the ACM on Management of Data 1 (1), 1-27, 2023 | 14 | 2023 |
| LMFAO: An engine for batches of group-by aggregates M Schleich, D Olteanu arXiv preprint arXiv:2008.08657, 2020 | 13 | 2020 |
| An intermediate representation for hybrid database and machine learning workloads A Shaikhha, M Schleich, D Olteanu Proceedings of the VLDB Endowment 14 (12), 2831-2834, 2021 | 10 | 2021 |
| In-database factorized learning H Ngo, X Nguyen, D Olteanu, M Schleich CEUR Workshop Proceedings 1912, 2017 | 9 | 2017 |
| Computing rule-based explanations by leveraging counterfactuals Z Geng, M Schleich, D Suciu arXiv preprint arXiv:2210.17071, 2022 | 4 | 2022 |
| Structure-aware machine learning over multi-relational databases M Schleich Proceedings of the 2021 International Conference on Management of Data, 6-7, 2021 | 3 | 2021 |
Dan OlteanuProfessor of Computer Science, University of ZurichAdresse e-mail validée de ifi.uzh.ch
