| Accelerating human-in-the-loop machine learning: Challenges and opportunities D Xin, L Ma, J Liu, S Macke, S Song, A Parameswaran Proceedings of the Second Workshop on Data Management for End-To-End Machine …, 2018 | 206 | 2018 |
| Towards Scalable Dataframe Systems D Petersohn, S Macke, D Xin, W Ma, D Lee, X Mo, JE Gonzalez, ... arXiv preprint arXiv:2001.00888, 2020 | 146 | 2020 |
| A Human-in-the-loop Perspective on AutoML: Milestones and the Road Ahead. DJL Lee, S Macke, D Xin, A Lee, S Huang, AG Parameswaran IEEE Data Eng. Bull. 42 (2), 59-70, 2019 | 103 | 2019 |
| Helix: Holistic optimization for accelerating iterative machine learning D Xin, S Macke, L Ma, J Liu, S Song, A Parameswaran arXiv preprint arXiv:1812.05762, 2018 | 87 | 2018 |
| Unsupervised approaches to detecting anomalous behavior in the bitcoin transaction network J Hirshman, Y Huang, S Macke 3rd ed. Technical report, Stanford University, 2013 | 66 | 2013 |
| Fine-grained lineage for safer notebook interactions S Macke, H Gong, DJL Lee, A Head, D Xin, A Parameswaran arXiv preprint arXiv:2012.06981, 2020 | 49 | 2020 |
| Helix: accelerating human-in-the-loop machine learning D Xin, L Ma, J Liu, S Macke, S Song, A Parameswaran arXiv preprint arXiv:1808.01095, 2018 | 47 | 2018 |
| Lifting the curse of multidimensional data with learned existence indexes S Macke, A Beutel, T Kraska, M Sathiamoorthy, DZ Cheng, EH Chi Workshop on ML for Systems at NeurIPS, 2018 | 29 | 2018 |
| Adaptive sampling for rapidly matching histograms S Macke, Y Zhang, S Huang, A Parameswaran arXiv preprint arXiv:1708.05918, 2017 | 27 | 2017 |
| Holistic optimization for accelerating iterative machine learning AG Parameswaran, S Macke, DS Xin US Patent 11,620,574, 2023 | 23 | 2023 |
| Bolt-on, compact, and rapid program slicing for notebooks S Shankar, S Macke, S Chasins, A Head, A Parameswaran Proceedings of the VLDB Endowment 15 (13), 4038-4047, 2022 | 20 | 2022 |
| Deep sentencelevel authorship attribution S Macke, J Hirshman Stanford University, 2015 | 11 | 2015 |
| Systematic redaction for neuroimage data M Matlock, N Schimke, L Kong, S Macke, J Hale International Journal of Computational Models and Algorithms in Medicine …, 2012 | 10 | 2012 |
| Rapid approximate aggregation with distribution-sensitive interval guarantees S Macke, M Aliakbarpour, I Diakonikolas, A Parameswaran, R Rubinfeld 2021 IEEE 37th International Conference on Data Engineering (ICDE), 1703-1714, 2021 | 7 | 2021 |
| Entropy-based subword mining with an application to word embeddings A El-Kishky, FF Xu, A Zhang, S Macke, J Han Proceedings of the Second Workshop on Subword/Character LEvel Models, 12-21, 2018 | 7 | 2018 |
| Automating State Management in Computational Notebooks. S Macke CIDR, 2021 | 2 | 2021 |
| Towards a Theory of DATA-DIFF: Optimal Synthesis of Succinct Data Modification Scripts T Wattanawaroon, S Macke, A Parameswaran arXiv preprint arXiv:1801.06258, 2018 | 2 | 2018 |
| Bolt-on, Compact, and Rapid Program Slicing for Notebooks [Technical Report] S Shankar, S Macke, S Chasins, A Head, A Parameswaran Technical report, 2022 | 1 | 2022 |
| LEVERAGING DISTRIBUTIONAL CONTEXT FOR SAFE AND INTERACTIVE DATA SCIENCE AT SCALE ST MACKE | | 2021 |
| Generalized Cost Analysis for Decentralized Search over Metric-embedded Networks S Macke | | |
Aditya ParameswaranAssociate Professor, EECS, UC BerkeleyVerified email at berkeley.edu
