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Sketching via Hashing: From Heavy Hitters to Compressive Sensing to Sparse Fourier Transform

Summary: Survey of hashing-based sketching primitives that enable single-pass, sublinear-space approximation of counts and heavy hitters in data streams. Explores how these hash-sketch variants unify and propel algorithmic advances in compressive sensing, dimensionality reduction, and sparse FFT. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1599
Venue
PODS
Year
2013
Pagerank
5.3251649e-05
Overall Rank
9,084 | 37.68%
DOI
10.1145/2463664.2465217

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{indyk_pods13,
        address = {New York, NY, USA},
        series = {{PODS} '13},
        title = {{Sketching via Hashing: From Heavy Hitters to Compressive Sensing to Sparse Fourier Transform}},
        url = {https://dl.acm.org/doi/10.1145/2463664.2465217},
        doi = {10.1145/2463664.2465217},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Indyk, Piotr},
        year = {2013}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
11,123 Streaming Algorithms with Few State Changes 2024 PODS 5.093636e-05
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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
577 Computing Iceberg Queries Efficiently 1998 VLDB 0.00016235949
838 What’s Hot and What’s Not: Tracking Most Frequent Items Dynamically 2003 PODS 0.0001370404
862 Spectral Bloom Filters 2003 SIGMOD 0.00013532857
Previous Page 1 / 1 Next

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