Space-optimal Heavy Hitters with Strong Error Bounds
Summary: Shows FREQUENT/SpaceSaving get a tail guarantee: per-item error depends only on the L1 mass of the tail, not on top frequencies, making them space-optimal under this stronger bound. Implies O(k) space sparse recovery with near-optimal L1 error (improving O(k log n)) and gives guarantees for Zipfian data and mergeable summaries. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Radu Berinde
- 2. Graham Cormode
- 3. Piotr Indyk
- 4. Martin J. Strauss
Incoming Citations (Sorted by Pagerank)
Showing 14 of 14 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 166 | Approximate Frequency Counts over Data Streams | 2002 | VLDB | 0.00039361552 |
| 472 | Bottom-Up Computation of Sparse and Iceberg CUBEs | 1999 | SIGMOD | 0.00022346384 |
| 597 | Computing Iceberg Queries Efficiently | 1998 | VLDB | 0.00019475592 |
| 835 | Finding Frequent Items in Data Streams | 2008 | VLDB | 0.00016109621 |
| 1,955 | Efficient Computation of Iceberg Cubes with Complex Measures | 2001 | SIGMOD | 9.9629452e-05 |
| 3,660 | Space Complexity of Hierarchical Heavy Hitters in Multi-Dimensional Data Streams | 2005 | PODS | 6.8691367e-05 |
| 5,016 | Finding Hierarchical Heavy Hitters in Data Streams | 2003 | VLDB | 5.7580375e-05 |
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