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Parimarjan Negi
Parimarjan Negi
PhD Student, MIT
Verified email at mit.edu - Homepage
Title
Cited by
Cited by
Year
Neo: A learned query optimizer
R Marcus, P Negi, H Mao, C Zhang, M Alizadeh, T Kraska, ...
arXiv preprint arXiv:1904.03711, 2019
3772019
High throughput cryptocurrency routing in payment channel networks
V Sivaraman, SB Venkatakrishnan, K Ruan, P Negi, L Yang, R Mittal, ...
17th USENIX Symposium on Networked Systems Design and Implementation (NSDI …, 2020
1602020
Bao: Making learned query optimization practical
R Marcus, P Negi, H Mao, N Tatbul, M Alizadeh, T Kraska
Proceedings of the 2021 International Conference on Management of Data, 1275 …, 2021
1562021
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
962018
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
902019
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
522021
Bao: Learning to steer query optimizers
R Marcus, P Negi, H Mao, N Tatbul, M Alizadeh, T Kraska
arXiv preprint arXiv:2004.03814, 2020
442020
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
412020
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
322021
K-means++ vs. Behavioral Biometrics: One Loop to Rule Them All.
P Negi, P Sharma, V Jain, B Bahmani
NDSS, 2018
262018
Robust query driven cardinality estimation under changing workloads
P Negi, Z Wu, A Kipf, N Tatbul, R Marcus, S Madden, T Kraska, ...
Proceedings of the VLDB Endowment 16 (6), 1520-1533, 2023
152023
FactorJoin: a new cardinality estimation framework for join queries
Z Wu, P Negi, M Alizadeh, T Kraska, S Madden
Proceedings of the ACM on Management of Data 1 (1), 1-27, 2023
132023
Neo: A Learned query optimizer. PVLDB 12, 11 (2018), 1705–1718
R Marcus, P Negi, H Mao, C Zhang, M Alizadeh, T Kraska, ...
81904
Adversarial machine learning against keystroke dynamics
P Negi, A Sharma, C Robustness
Stanford, 2017
52017
Unshackling Database Benchmarking from Synthetic Workloads
P Negi, L Bindschaedler, M Alizadeh, T Kraska, J Leeka, A Gruenheid, ...
2023 IEEE 39th International Conference on Data Engineering (ICDE), 3659-3662, 2023
12023
Stage: Query Execution Time Prediction in Amazon Redshift
Z Wu, R Marcus, Z Liu, P Negi, V Nathan, P Pfeil, G Saxena, M Rahman, ...
arXiv preprint arXiv:2403.02286, 2024
2024
Machine Learning for Out of Distribution Database Workloads
P Negi
Massachusetts Institute of Technology, 2024
2024
Some Cardinality Estimates are More Equal than Others
P Negi
Massachusetts Institute of Technology, 2022
2022
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Articles 1–18