| Neo: A learned query optimizer R Marcus, P Negi, H Mao, C Zhang, M Alizadeh, T Kraska, ... arXiv preprint arXiv:1904.03711, 2019 | 271 | 2019 |
| High throughput cryptocurrency routing in payment channel networks V Sivaraman, SB Venkatakrishnan, K Ruan, P Negi, L Yang, R Mittal, ... USENIX Symposium on Networked Systems Design and Implementation (NSDI), 2020 | 116 | 2020 |
| Bao: Making learned query optimization practical R Marcus, P Negi, H Mao, N Tatbul, M Alizadeh, T Kraska ACM SIGMOD Record 51 (1), 6-13, 2022 | 78 | 2022 |
| Evaluating end-to-end optimization for data analytics applications in weld S Palkar, J Thomas, D Narayanan, P Thaker, R Palamuttam, P Negi, ... Proceedings of the VLDB Endowment 11 (9), 1002-1015, 2018 | 73 | 2018 |
| Park: An open platform for learning-augmented computer systems H Mao, P Negi, A Narayan, H Wang, J Yang, H Wang, R Marcus, ... Advances in Neural Information Processing Systems 32, 2019 | 69 | 2019 |
| Bao: Learning to steer query optimizers R Marcus, P Negi, H Mao, N Tatbul, M Alizadeh, T Kraska arXiv preprint arXiv:2004.03814, 2020 | 34 | 2020 |
| Cost-guided cardinality estimation: Focus where it matters P Negi, R Marcus, H Mao, N Tatbul, T Kraska, M Alizadeh 2020 IEEE 36th International Conference on Data Engineering Workshops (ICDEW …, 2020 | 28 | 2020 |
| Flow-loss: Learning cardinality estimates that matter P Negi, R Marcus, A Kipf, H Mao, N Tatbul, T Kraska, M Alizadeh arXiv preprint arXiv:2101.04964, 2021 | 26 | 2021 |
| K-means++ vs. Behavioral Biometrics: One Loop to Rule Them All. P Negi, P Sharma, V Jain, B Bahmani NDSS, 2018 | 22 | 2018 |
| Steering query optimizers: A practical take on big data workloads P Negi, M Interlandi, R Marcus, M Alizadeh, T Kraska, M Friedman, ... Proceedings of the 2021 International Conference on Management of Data, 2557 …, 2021 | 20 | 2021 |
| Adversarial machine learning against keystroke dynamics P Negi, A Sharma, C Robustness Stanford, 2017 | 5 | 2017 |
| Neo: A Learned query optimizer. PVLDB 12, 11 (2018), 1705–1718 R Marcus, P Negi, H Mao, C Zhang, M Alizadeh, T Kraska, ... | 5 | 1904 |
| FactorJoin: A New Cardinality Estimation Framework for Join Queries Z Wu, P Negi, M Alizadeh, T Kraska, S Madden arXiv preprint arXiv:2212.05526, 2022 | | 2022 |
| Some Cardinality Estimates are More Equal than Others P Negi Massachusetts Institute of Technology, 2022 | | 2022 |
