Sampling Methods for Inner Product Sketching
Summary: Introduce two linear-time sampling-based inner-product sketches (threshold and priority sampling) that are far cheaper than Bessa et al.'s coordinated weighted sampling and empirically outperform JL/CountSketch. Provide new approximation guarantees and state-of-the-art accuracy for tasks like estimating column correlations in unjoined tables. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Majid Daliri (New York University)
- 2. Juliana Freire (New York University)
- 3. Christopher Musco (New York University)
- 4. Aécio Santos (New York University)
- 5. Haoxiang Zhang (New York University)
BibTeX Citation
@article{daliri_vldb24,
title = {{Sampling Methods for Inner Product Sketching}},
author = {Daliri, Majid and Freire, Juliana and Musco, Christopher and Santos, Aécio and Zhang, Haoxiang},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {9},
pages = {2185--2197},
doi = {10.14778/3665844.3665850},
url = {https://doi.org/10.14778/3665844.3665850},
year = {2024}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,293 | Magneto: Combining Small and Large Language Models for Schema Matching | 2025 | VLDB | 6.279939e-05 |
| 10,162 | On Sketching Trimmed Statistics | 2026 | PODS | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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