Maintaining Variance and k–Medians over Data Stream Windows
Summary: Sliding-window streaming algorithms: variance estimator with relative error ε using O((1/ε^2) log N) space. Also a constant-factor approximate k‑median for last N points using O((1/τ) k^4 N^{2τ} log^2 N) space, τ<1/2 trades space for approximation O(2^{O(1/τ)}). (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Brian Babcock (Stanford University)
- 2. Mayur Datar (Stanford University)
- 3. Rajeev Motwani (Stanford University)
- 4. Liadan O'Callaghan (Stanford University)
BibTeX Citation
@inproceedings{babcock_pods03,
address = {New York, NY, USA},
series = {{PODS} '03},
title = {{Maintaining Variance and k–Medians over Data Stream Windows}},
url = {https://dl.acm.org/doi/10.1145/773153.773176},
doi = {10.1145/773153.773176},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Babcock, Brian and Datar, Mayur and Motwani, Rajeev and O'Callaghan, Liadan},
year = {2003}
}
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 26 | Models and Issues in Data Stream Systems | 2002 | PODS | 0.00052982574 |
| 31 | BIRCH: An Efficient Data Clustering Method for Very Large Databases | 1996 | SIGMOD | 0.00050347119 |
| 311 | Surfing Wavelets on Streams: One-Pass Summaries for Approximate Aggregate Queries | 2001 | VLDB | 0.00021760621 |
| 351 | CURE: An Efficient Clustering Algorithm for Large Databases | 1998 | SIGMOD | 0.00020424271 |
| 4,222 | Density Biased Sampling: An Improved Method for Data Mining and Clustering | 2000 | SIGMOD | 6.8227421e-05 |
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