| Skinnerdb: Regret-bounded query evaluation via reinforcement learning I Trummer, J Wang, Z Wei, D Maram, S Moseley, S Jo, J Antonakakis, ... ACM Transactions on Database Systems (TODS) 46 (3), 1-45, 2021 | 126 | 2021 |
| Skinnerdb: regret-bounded query evaluation via reinforcement learning I Trummer, S Moseley, D Maram, S Jo, J Antonakakis Proceedings of the VLDB Endowment 11 (12), 2074-2077, 2018 | 44 | 2018 |
| Verifying text summaries of relational data sets S Jo, I Trummer, W Yu, X Wang, C Yu, D Liu, N Mehta Proceedings of the 2019 International Conference on Management of Data, 299-316, 2019 | 34* | 2019 |
| ISUM: Efficiently compressing large and complex workloads for scalable index tuning T Siddiqui, S Jo, W Wu, C Wang, V Narasayya, S Chaudhuri Proceedings of the 2022 International Conference on Management of Data, 660-673, 2022 | 25 | 2022 |
| Mining an" anti-knowledge base" from Wikipedia updates with applications to fact checking and beyond G Karagiannis, I Trummer, S Jo, S Khandelwal, X Wang, C Yu Proceedings of the VLDB Endowment 13 (4), 561-573, 2019 | 24 | 2019 |
| Supervised belief propagation: Scalable supervised inference on attributed networks J Yoo, S Jo, U Kang 2017 IEEE International Conference on Data Mining (ICDM), 595-604, 2017 | 21 | 2017 |
| Fast and scalable distributed loopy belief propagation on real-world graphs S Jo, J Yoo, U Kang Proceedings of the Eleventh ACM International Conference on Web Search and …, 2018 | 17 | 2018 |
| Demonstration of thalamusdb: answering complex sql queries with natural language predicates on multi-modal data S Jo, I Trummer Companion of the 2023 International Conference on Management of Data, 179-182, 2023 | 14 | 2023 |
| Aggchecker: A fact-checking system for text summaries of relational data sets S Jo, I Trummer, W Yu, X Wang, C Yu, D Liu, N Mehta Proceedings of the VLDB Endowment 12 (12), 1938-1941, 2019 | 13 | 2019 |
| BitGourmet: Deterministic Approximation via Optimized Bit Selection S Jo, I Trummer The Conference on Innovative Data Systems Research (CIDR), 2020 | 6 | 2020 |
| Thalamusdb: Approximate query processing on multi-modal data S Jo, I Trummer Proceedings of the ACM on Management of Data 2 (3), 1-26, 2024 | 2 | 2024 |
| Demonstration of ScroogeDB: Getting more bang for the buck with deterministic approximation in the cloud S Jo, J Pei, I Trummer Proceedings of the VLDB Endowment 13 (12), 2961-2964, 2020 | 2 | 2020 |
| Compressing workloads for scalable index tuning TA Siddiqui, JO Saehan, W Wu, C Wang, VR Narasayya, S Chaudhuri US Patent 12,105,713, 2024 | | 2024 |
| SMART: Automatically Scaling Down Language Models with Accuracy Guarantees for Reduced Processing Fees S Jo, I Trummer arXiv preprint arXiv:2403.13835, 2024 | | 2024 |
| ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning (Extended Version) T Siddiqui, S Jo, W Wu, C Wang, V Narasayya, S Chaudhuri | | 2022 |
| Demonstration of BitGourmet: Data Analysis via Deterministic Approximation S Jo, I Trummer Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020 | | 2020 |
Immanuel TrummerProfessor for Computer Science, Cornell UniversityZweryfikowany adres z cornell.edu
