| Neo: A learned query optimizer R Marcus, P Negi, H Mao, C Zhang, M Alizadeh, T Kraska, ... Proceedings of the VLDB Endowment 12 (11), 1705-1718,, 2019 | 481 | 2019 |
| Buffer Pool Aware Query Scheduling via Deep Reinforcement Learning C Zhang, R Marcus, A Kleiman, O Papaemmanouil AIDB'20 Proceedings of 2nd International Workshop on Applied AI for …, 2020 | 18 | 2020 |
| Neo: A Learned Query Optimizer. PVLDB 12, 11 (2019), 1705–1718 RC Marcus, P Negi, H Mao, C Zhang, M Alizadeh, T Kraska, ... | 5 | 2019 |
| Candidate projection enumeration based query response generation C Zhang, Z Peng, Y Bei, O Papaemmanouil US Patent 11,288,266, 2022 | 4 | 2022 |
| Making Data Clouds Smarter at Keebo: Automated Warehouse Optimization using Data Learning B Mozafari, RA Burcuta, A Cabrera, A Constantin, D Francis, D Grömling, ... Proceedings of the 2023 International Conference on Management of Data, 2023 | 3 | 2023 |
| Nashdb: fragmentation, replication, and provisioning using economic methods R Marcus, C Zhang, S Yu, G Kao, O Papaemmanouil Proceedings of the VLDB Endowment 12 (12), 1830-1833, 2019 | 1 | 2019 |
| Multi-agent Databases via Independent Learning C Zhang, O Papaemmanouil, J P.Hanna, A Akella AIDB'22 Proceedings of of 4th International Workshop on Applied AI for …, 2022 | | 2022 |
Olga PapaemmanouilAssociate Professor at Brandeis UniversityEmail được xác minh tại cs.brandeis.edu