Sketching Data Structures

Sketching Data Structures is a class of probabilistic data structures designed to summarize large data streams in sublinear space by capturing essential statistical properties, enabling approximate query responses with bounded error guarantees.

48

Publications

3K

Citations

125

Authors

64

Institutions

Publications per year

2017–2026

16

Authors

125

  1. TY
    Tong Yang

    Peking University, China

    6 publications · 333 citations

    6

    h-index

  2. PI
    Piotr Indyk

    Massachusetts Institute of Technology, United States

    4 publications · 943 citations

    4

    h-index

  3. HD
    Hal Daumé

    University of Maryland, College Park, United States

    3 publications · 63 citations

    3

    h-index

  4. MG
    Minos Garofalakis

    Technical University of Crete, Greece

    3 publications · 604 citations

    3

    h-index

  5. GC
    Graham Cormode

    AT&T (United States), United States

    3 publications · 531 citations

    3

    h-index

1–5 of 125

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 4 publications · 298 citations

    4

    h-index

  2. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 3 publications · 102 citations

    3

    h-index

  3. Computer Networks

    2 publications · 51 citations

    2

    h-index

  4. IEEE/ACM Transactions on Networking

    TON · 2 publications · 60 citations

    2

    h-index

  5. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 1 publications · 24 citations

    1

    h-index

1–5