Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process-Reference-Cited by-同舟云学术

Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process

Published:2022-06-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2022 International Conference on Management of Data
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Author:

Zhao Kangfei¹,Yu Jeffrey Xu¹,He Zongyan¹,Li Rui¹,Zhang Hao¹

Affiliation:

1. The Chinese University of Hong Kong, Hong Kong S. A. R., China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3514221.3526156

Reference76 articles.

1. Pytorch. https://github.com/pytorch/pytorch. Pytorch. https://github.com/pytorch/pytorch.

2. The Aqua approximate query answering system

3. Knowing when you're wrong

4. Automatic Database Management System Tuning Through Large-scale Machine Learning

5. C. M. Bishop . Pattern recognition and machine learning , 5 th Edition. Information science and statistics. Springer , 2007 . C. M. Bishop. Pattern recognition and machine learning, 5th Edition. Information science and statistics. Springer, 2007.

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