Space- and Time-Efficient Deterministic Algorithms for Biased Quantiles over Data Streams
Summary: First deterministic one-pass algorithms for biased quantiles on data streams, providing skew-aware accuracy (more precise at extremes) with near-optimal sublinear space. Amortized updates are near-constant, practical and empirically use less space and are fast to maintain. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Graham Cormode
- 2. Flip Korn
- 3. S. Muthukrishnan
- 4. Divesh Srivastava
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 43 | Models and Issues in Data Stream Systems | 2002 | PODS | 0.00072660894 |
| 126 | Space-Efficient Online Computation of Quantile Summaries | 2001 | SIGMOD | 0.00044753012 |
| 446 | Random Sampling Techniques for Space Efficient Online Computation of Order Statistics of Large Datasets | 1999 | SIGMOD | 0.00023002059 |
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