Reproducibility Report for ACM SIGMOD 2024 Paper: 'Can Learned Indexes be Built Efficiently? A Deep Dive into Sampling Trade-offs'
In general, most of the main experiments in the paper ''Can Learned Indexes be Built Efficiently? A Deep Dive into Sampling Trade-offs'' can be successfully reproduced.
Authors
- Yuanhui Luo (ORCID: https://orcid.org/0009-0003-8361-6766)
- Yihao Liu (ORCID: https://orcid.org/0009-0004-4623-5240)
- Minguk Choi (ORCID: https://orcid.org/0009-0003-4030-9344)
Institutions
- Renmin University of China (CN)
- Dankook University (KR)
- Tsinghua University (CN)
Publication Details
- Published
- 2025-03-21
- DOI
- https://doi.org/10.1145/3687998.3717055
- Primary Topic
- Machine Learning and Data Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00