| Neo: A learned query optimizer R Marcus, P Negi, H Mao, C Zhang, M Alizadeh, T Kraska, ... arXiv preprint arXiv:1904.03711, 2019 | 403 | 2019 |
| Overview of data exploration techniques S Idreos, O Papaemmanouil, S Chaudhuri Proceedings of the 2015 ACM SIGMOD international conference on management of …, 2015 | 340 | 2015 |
| Deep reinforcement learning for join order enumeration R Marcus, O Papaemmanouil Proceedings of the First International Workshop on Exploiting Artificial …, 2018 | 260 | 2018 |
| Performance prediction for concurrent database workloads J Duggan, U Cetintemel, O Papaemmanouil, E Upfal Proceedings of the 2011 ACM SIGMOD International Conference on Management of …, 2011 | 196 | 2011 |
| Explore-by-example: An automatic query steering framework for interactive data exploration K Dimitriadou, O Papaemmanouil, Y Diao Proceedings of the 2014 ACM SIGMOD international conference on Management of …, 2014 | 190 | 2014 |
| Plan-structured deep neural network models for query performance prediction R Marcus, O Papaemmanouil arXiv preprint arXiv:1902.00132, 2019 | 143 | 2019 |
| Distributed operation in the borealis stream processing engine Y Ahmad, B Berg, U Cetintemel, M Humphrey, JH Hwang, A Jhingran, ... Proceedings of the 2005 ACM SIGMOD international conference on Management of …, 2005 | 131 | 2005 |
| AIDE: an active learning-based approach for interactive data exploration K Dimitriadou, O Papaemmanouil, Y Diao IEEE Transactions on Knowledge and Data Engineering 28 (11), 2842-2856, 2016 | 104 | 2016 |
| Query Steering for Interactive Data Exploration. U Cetintemel, M Cherniack, JA DeBrabant, Y Diao, K Dimitriadou, ... CIDR, 2013 | 102 | 2013 |
| Semcast: Semantic multicast for content-based data dissemination O Papaemmanouil, U Cetintemel 21st International Conference on Data Engineering (ICDE'05), 242-253, 2005 | 99 | 2005 |
| Towards a hands-free query optimizer through deep learning R Marcus, O Papaemmanouil arXiv preprint arXiv:1809.10212, 2018 | 91 | 2018 |
| A generic auto-provisioning framework for cloud databases J Rogers, O Papaemmanouil, U Cetintemel 2010 IEEE 26th International Conference on Data Engineering Workshops (ICDEW …, 2010 | 67 | 2010 |
| Wisedb: A learning-based workload management advisor for cloud databases R Marcus, O Papaemmanouil arXiv preprint arXiv:1601.08221, 2016 | 56 | 2016 |
| Query Deployment Plan For A Distributed Shared Stream Processing System O Papaemmanouil, S Basu, S Banerjee US Patent App. 12/244,878, 2009 | 50 | 2009 |
| Skew-aware join optimization for array databases J Duggan, O Papaemmanouil, L Battle, M Stonebraker Proceedings of the 2015 ACM SIGMOD International Conference on Management of …, 2015 | 45 | 2015 |
| June 2005. Distributed operation in the Borealis Stream Processing Engine. Demonstration Y Ahmad, B Berg, U Çetintemel, M Humphrey, J Hwang, A Jhingran, ... ACM SIGMOD International Conference on Management of Data (SIGMOD'05), 0 | 45 | |
| Contender: A Resource Modeling Approach for Concurrent Query Performance Prediction. J Duggan, O Papaemmanouil, U Cetintemel, E Upfal EDBT, 109-120, 2014 | 44 | 2014 |
| Extensible optimization in overlay dissemination trees O Papaemmanouil, Y Ahmad, U Çetintemel, J Jannotti, Y Yildirim Proceedings of the 2006 ACM SIGMOD international conference on Management of …, 2006 | 33 | 2006 |
| NashDB: an end-to-end economic method for elastic database fragmentation, replication, and provisioning R Marcus, O Papaemmanouil, S Semenova, S Garber Proceedings of the 2018 International Conference on Management of Data, 1253 …, 2018 | 31 | 2018 |
| Releasing Cloud Databases for the Chains of Performance Prediction Models. R Marcus, O Papaemmanouil CIDR, 2017 | 29 | 2017 |
Ryan MarcusUniversity of Pennsylvania在 seas.upenn.edu 的电子邮件经过验证
