| Macrobase: Prioritizing attention in fast data P Bailis, E Gan, S Madden, D Narayanan, K Rong, S Suri Proceedings of the 2017 ACM International Conference on Management of Data …, 2017 | 198 | 2017 |
| ASAP: prioritizing attention via time series smoothing K Rong, P Bailis arXiv preprint arXiv:1703.00983, 2017 | 53 | 2017 |
| Locality-sensitive hashing for earthquake detection: A case study of scaling data-driven science K Rong, CE Yoon, KJ Bergen, H Elezabi, P Bailis, P Levis, GC Beroza arXiv preprint arXiv:1803.09835, 2018 | 51 | 2018 |
| Rehashing kernel evaluation in high dimensions P Siminelakis, K Rong, P Bailis, M Charikar, P Levis International Conference on Machine Learning, 5789-5798, 2019 | 48 | 2019 |
| Prioritizing attention in fast data: Principles and promise P Bailis, E Gan, K Rong, S Suri, S InfoLab CIDR Google Scholar 10 (3035918.3035928), 2017 | 24 | 2017 |
| Macrobase: Prioritizing attention in fast data F Abuzaid, P Bailis, J Ding, E Gan, S Madden, D Narayanan, K Rong, ... ACM Transactions on Database Systems (TODS) 43 (4), 1-45, 2018 | 18 | 2018 |
| Unsupervised large‐scale search for similar earthquake signals CE Yoon, KJ Bergen, K Rong, H Elezabi, WL Ellsworth, GC Beroza, ... Bulletin of the Seismological Society of America 109 (4), 1451-1468, 2019 | 15 | 2019 |
| Approximate partition selection for big-data workloads using summary statistics K Rong, Y Lu, P Bailis, S Kandula, P Levis arXiv preprint arXiv:2008.10569, 2020 | 12 | 2020 |
| Diffprep: Differentiable data preprocessing pipeline search for learning over tabular data P Li, Z Chen, X Chu, K Rong Proceedings of the ACM on Management of Data 1 (2), 1-26, 2023 | 8 | 2023 |
| Crosstrainer: Practical domain adaptation with loss reweighting J Chen, E Gan, K Rong, S Suri, P Bailis Proceedings of the 3rd International Workshop on Data Management for End-to …, 2019 | 7 | 2019 |
| MacroBase, A Fast Data Analysis Engine P Bailis, E Gan, K Rong, S Suri Proceedings of the 2017 ACM International Conference on Management of Data …, 2017 | 4 | 2017 |
| Scaling a Declarative Cluster Manager Architecture with Query Optimization Techniques K Rong, M Budiu, A Skiadopoulos, L Suresh, A Tai Proceedings of the VLDB Endowment 16 (10), 2618-2631, 2023 | 3* | 2023 |
| Inshrinkerator: Compressing Deep Learning Training Checkpoints via Dynamic Quantization A Agrawal, S Reddy, S Bhattamishra, VPS Nookala, V Vashishth, K Rong, ... Proceedings of the 2024 ACM Symposium on Cloud Computing, 1012-1031, 2024 | 2* | 2024 |
| Rethinking Similarity Search: Embracing Smarter Mechanisms over Smarter Data R Wu, J Meng, JJ Xu, H Wang, K Rong arXiv preprint arXiv:2308.00909, 2023 | 1 | 2023 |
| Interactive Demonstration of EVA GT Kakkar, A Rajoria, MP Kalluraya, A Raju, J Cao, K Rong, J Arulraj Proceedings of the VLDB Endowment 16 (12), 4082-4085, 2023 | 1 | 2023 |
| Improving Computational and Human Efficiency in Large-Scale Data Analytics K Rong Stanford University, 2021 | 1 | 2021 |
| SketchQL: Video Moment Querying with a Visual Query Interface R Wu, P Chunduri, A Payani, X Chu, J Arulraj, K Rong Proceedings of the ACM on Management of Data 2 (4), 1-27, 2024 | | 2024 |
| Lotus: Characterization of Machine Learning Preprocessing Pipelines via Framework and Hardware Profiling R Bachkaniwala, H Lanka, K Rong, A Gavrilovska 2024 IEEE International Symposium on Workload Characterization (IISWC), 30-43, 2024 | | 2024 |
| Demonstration of VCR: A Tabular Data Slicing Approach to Understanding Object Detection Model Performance JJ Xu, S Dhanani, JP Ono, W He, L Ren, K Rong Proceedings of the VLDB Endowment 17 (12), 4453-4456, 2024 | | 2024 |
| Eighth Workshop on Human-In-the-Loop Data Analytics (HILDA) JD Fekete, K Rong, B Omidvar-Tehrani, R Shraga Companion of the 2024 International Conference on Management of Data, 657-658, 2024 | | 2024 |
Peter BailisGoogleVerified email at google.com
