Double-Anonymous Sketch: Achieving Top-K-fairness for Finding Global Top-K Frequent Items
Summary: Proposes Double-Anonymous sketch to compute global top-K across disjoint streams with top-K-fairness. Leverages double-anonymity, hot panning, and early freezing; provides theoretical guarantees and extensive experiments showing substantial error reductions vs state-of-the-art; open-source code. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yikai Zhao
- 2. Wenchen Han
- 3. Zheng Zhong
- 4. Yinda Zhang
- 5. Tong Yang
- 6. Bin Cui
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,034 | SieveSketch: A Fine-grained and Adaptive Sketch Framework for Accurate Frequency Estimation | 2026 | SIGMOD | 4.1945683e-05 |
| 10,315 | CounterSnake: A lossless and generalized compression framework for diverse sketches | 2026 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 24 of 24 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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