| Probase: A probabilistic taxonomy for text understanding W Wu, H Li, H Wang, KQ Zhu Proceedings of the 2012 ACM SIGMOD International Conference on Management of …, 2012 | 1098 | 2012 |
| Predicting query execution time: Are optimizer cost models really unusable? W Wu, Y Chi, S Zhu, J Tatemura, H Hacigümüs, JF Naughton 2013 IEEE 29th International Conference on Data Engineering (ICDE), 1081-1092, 2013 | 266 | 2013 |
| Ai meets ai: Leveraging query executions to improve index recommendations B Ding, S Das, R Marcus, W Wu, S Chaudhuri, VR Narasayya Proceedings of the 2019 International Conference on Management of Data, 1241 …, 2019 | 156 | 2019 |
| Towards demystifying serverless machine learning training J Jiang, S Gan, Y Liu, F Wang, G Alonso, A Klimovic, A Singla, W Wu, ... Proceedings of the 2021 International Conference on Management of Data, 857-871, 2021 | 151 | 2021 |
| K-symmetry model for identity anonymization in social networks W Wu, Y Xiao, W Wang, Z He, Z Wang Proceedings of the 13th international conference on extending database …, 2010 | 137 | 2010 |
| Towards predicting query execution time for concurrent and dynamic database workloads W Wu, Y Chi, H Hacígümüş, JF Naughton Proceedings of the VLDB Endowment 6 (10), 925-936, 2013 | 123 | 2013 |
| A Data Quality-Driven View of MLOps CZ Cedric Renggli, Luka Rimanic, Nezihe Merve Gurel, Bojan Karlas, Wentao Wu IEEE Data Engineering Bulletin 44 (1), 11-23, 2021 | 109* | 2021 |
| Ease. ml: Towards multi-tenant resource sharing for machine learning workloads T Li, J Zhong, J Liu, W Wu, C Zhang Proceedings of the VLDB Endowment 11 (5), 607-620, 2018 | 109 | 2018 |
| Sampling-Based Query Re-Optimization W Wu, JF Naughton, H Singh Proceedings of the ACM SIGMOD International Conference on Management of Data …, 2016 | 97 | 2016 |
| Semantic bootstrapping: a theoretical perspective W Wu, H Li, H Wang, KQ Zhu IEEE Transactions on Knowledge and Data Engineering 29 (2), 446-457, 2016 | 90* | 2016 |
| Efficiently indexing shortest paths by exploiting symmetry in graphs Y Xiao, W Wu, J Pei, W Wang, Z He Proceedings of the 12th International Conference on Extending Database …, 2009 | 90 | 2009 |
| Openbox: A generalized black-box optimization service Y Li, Y Shen, W Zhang, Y Chen, H Jiang, M Liu, J Jiang, J Gao, W Wu, ... Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021 | 82 | 2021 |
| Symmetry-based structure entropy of complex networks YH Xiao, WT Wu, H Wang, M Xiong, W Wang Physica A: Statistical Mechanics and its Applications 387 (11), 2611-2619, 2008 | 73 | 2008 |
| Mlog: Towards declarative in-database machine learning X Li, B Cui, Y Chen, W Wu, C Zhang Proceedings of the VLDB Endowment 10 (12), 1933-1936, 2017 | 72 | 2017 |
| Data Science Through the Looking Glass: Analysis of Millions of GitHub Notebooks and ML. NET Pipelines F Psallidas, Y Zhu, B Karlas, J Henkel, M Interlandi, S Krishnan, B Kroth, ... ACM SIGMOD Record 51 (2), 30-37, 2022 | 71 | 2022 |
| Nearest neighbor classifiers over incomplete information: From certain answers to certain predictions B Karlaš, P Li, R Wu, NM Gürel, X Chu, W Wu, C Zhang Proceedings of the VLDB Endowment 14 (3), 255-267, 2020 | 61 | 2020 |
| VolcanoML: speeding up end-to-end AutoML via scalable search space decomposition Y Li, Y Shen, W Zhang, J Jiang, Y Li, B Ding, J Zhou, Z Yang, W Wu, ... Proceedings of the VLDB Endowment 14 (11), 2167-2176, 2021 | 56 | 2021 |
| Data Debugging with Shapley Importance over Machine Learning Pipelines B Karlaš, D Dao, M Interlandi, S Schelter, W Wu, C Zhang The Twelfth International Conference on Learning Representations, 2023 | 55* | 2023 |
| Continuous Integration of Machine Learning Models with ease. ml/ci: Towards a Rigorous Yet Practical Treatment C Renggli, B Karlaš, B Ding, F Liu, K Schawinski, W Wu, C Zhang SysML Conference 2019, 2019 | 53 | 2019 |
| Uncertainty Aware Query Execution Time Prediction W Wu, X Wu, H Hacıgümüş, J Naughton Proceedings of the VLDB Endowment 7 (14), 1857 - 1868, 2014 | 53 | 2014 |
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