| Tfx: A tensorflow-based production-scale machine learning platform D Baylor, E Breck, HT Cheng, N Fiedel, CY Foo, Z Haque, S Haykal, ... Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017 | 472 | 2017 |
| Data validation for machine learning N Polyzotis, M Zinkevich, S Roy, E Breck, S Whang Proceedings of machine learning and systems 1, 334-347, 2019 | 380 | 2019 |
| Data management challenges in production machine learning N Polyzotis, S Roy, SE Whang, M Zinkevich Proceedings of the 2017 ACM International Conference on Management of Data …, 2017 | 246 | 2017 |
| Goods: Organizing google's datasets A Halevy, F Korn, NF Noy, C Olston, N Polyzotis, S Roy, SE Whang Proceedings of the 2016 International Conference on Management of Data, 795-806, 2016 | 246 | 2016 |
| Data lifecycle challenges in production machine learning: a survey N Polyzotis, S Roy, SE Whang, M Zinkevich ACM SIGMOD Record 47 (2), 17-28, 2018 | 235 | 2018 |
| Performance anomaly diagnosis AC Konig, I Dvorkin, M Kumar, S Roy US Patent 9,904,584, 2018 | 137 | 2018 |
| Pathways: Asynchronous distributed dataflow for ml P Barham, A Chowdhery, J Dean, S Ghemawat, S Hand, D Hurt, M Isard, ... Proceedings of Machine Learning and Systems 4, 430-449, 2022 | 129 | 2022 |
| Managing Google's data lake: an overview of the Goods system. AY Halevy, F Korn, NF Noy, C Olston, N Polyzotis, S Roy, SE Whang IEEE Data Eng. Bull. 39 (3), 5-14, 2016 | 93 | 2016 |
| Equality saturation for tensor graph superoptimization Y Yang, P Phothilimthana, Y Wang, M Willsey, S Roy, J Pienaar Proceedings of Machine Learning and Systems 3, 255-268, 2021 | 79 | 2021 |
| The Homeostasis Protocol: Avoiding Transaction Coordination Through Program Analysis S Roy, L Kot, G Bender, B Ding, H Hojjat, C Koch, N Foster, J Gehrke SIGMOD, 2015 | 78 | 2015 |
| A learned performance model for tensor processing units S Kaufman, P Phothilimthana, Y Zhou, C Mendis, S Roy, A Sabne, ... Proceedings of Machine Learning and Systems 3, 387-400, 2021 | 76 | 2021 |
| PerfAugur: Robust Diagnostics for Performance Anomalies in Cloud Services S Roy, C Konig, I Dvorkin, M Kumar International Conference on Data Engineering, 2015 | 73 | 2015 |
| Transferable graph optimizers for ml compilers Y Zhou, S Roy, A Abdolrashidi, D Wong, P Ma, Q Xu, H Liu, ... Advances in Neural Information Processing Systems 33, 13844-13855, 2020 | 56 | 2020 |
| Gdp: Generalized device placement for dataflow graphs Y Zhou, S Roy, A Abdolrashidi, D Wong, PC Ma, Q Xu, M Zhong, H Liu, ... arXiv preprint arXiv:1910.01578, 2019 | 48 | 2019 |
| Tensorflow data validation: Data analysis and validation in continuous ml pipelines E Caveness, PS GC, Z Peng, N Polyzotis, S Roy, M Zinkevich Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020 | 41 | 2020 |
| Quantum Databases S Roy, L Kot, C Koch CIDR, 2013 | 28 | 2013 |
| A flexible approach to autotuning multi-pass machine learning compilers PM Phothilimthana, A Sabne, N Sarda, KS Murthy, Y Zhou, ... 2021 30th International Conference on Parallel Architectures and Compilation …, 2021 | 27 | 2021 |
| A layout-aware physical design method for constructing feasible QCA circuits M Bubna, S Roy, N Shenoy, S Mazumdar Proceedings of the 18th ACM Great Lakes symposium on VLSI, 243-248, 2008 | 21 | 2008 |
| Entangled queries: enabling declarative data-driven coordination N Gupta, L Kot, S Roy, G Bender, J Gehrke, C Koch Proceedings of the 2011 international conference on Management of data, 673-684, 2011 | 20 | 2011 |
| Beyond isolation: Research opportunities in declarative data-driven coordination L Kot, N Gupta, S Roy, J Gehrke, C Koch ACM SIGMOD Record 39 (1), 27-32, 2010 | 17 | 2010 |
Steven Euijong WhangAssociate Professor with Tenure at KAIST EE and AIVerified email at kaist.ac.kr
