Kexin Rong
Kexin Rong
School of Computer Science, Georgia Institute of Technology
Verified email at - Homepage
Cited by
Cited by
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
ASAP: prioritizing attention via time series smoothing
K Rong, P Bailis
arXiv preprint arXiv:1703.00983, 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
Rehashing kernel evaluation in high dimensions
P Siminelakis, K Rong, P Bailis, M Charikar, P Levis
International Conference on Machine Learning, 5789-5798, 2019
Prioritizing attention in fast data: Principles and promise
P Bailis, E Gan, K Rong, S Suri
CIDR Google Scholar 10 (3035918.3035928), 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
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
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
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
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
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
Dynaquant: Compressing deep learning training checkpoints via dynamic quantization
A Agrawal, S Reddy, S Bhattamishra, VPS Nookala, V Vashishth, K Rong, ...
arXiv preprint arXiv:2306.11800, 2023
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
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
Improving Computational and Human Efficiency in Large-Scale Data Analytics
K Rong
Stanford University, 2021
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
SketchQL Demonstration: Zero-shot Video Moment Querying with Sketches
R Wu, P Chunduri, DJ Shah, AJ Aravind, A Payani, X Chu, J Arulraj, ...
arXiv preprint arXiv:2405.18334, 2024
Dynamic Data Layout Optimization with Worst-case Guarantees
K Rong, P Liu, SA Sonje, M Charikar
arXiv preprint arXiv:2405.04984, 2024
Falcon: Fair Active Learning using Multi-armed Bandits
KH Tae, H Zhang, J Park, K Rong, SE Whang
arXiv preprint arXiv:2401.12722, 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
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