Quantile Approximation

Quantile Approximation is a streaming algorithm that estimates order statistics of a data stream by maintaining a compact summary structure to approximate rank-based quantile values within bounded error and space complexity.

539

Publications

30.9K

Citations

991

Authors

560

Institutions

Publications per year

2017–2026

114

Authors

991

  1. GC
    Graham Cormode

    AT&T (United States), United States

    10 publications · 808 citations

    10

    h-index

  2. KY
    Ke Yi

    Hong Kong University of Science and Technology, Hong Kong SAR China

    8 publications · 507 citations

    8

    h-index

  3. MC
    Miklós Csörgő

    Carleton University, Canada

    7 publications · 476 citations

    7

    h-index

  4. RK
    Roger Koenker

    University of Illinois Urbana-Champaign, United States

    6 publications · 1.4K citations

    6

    h-index

  5. PG
    P. G. Sankaran

    Cochin University of Science and Technology, India

    6 publications · 224 citations

    6

    h-index

1–5 of 991

Venues

  1. Statistics & Probability Letters

    27 publications · 701 citations

    16

    h-index

  2. Computational Statistics & Data Analysis

    CSDA · 20 publications · 515 citations

    16

    h-index

  3. The Annals of Statistics

    18 publications · 2.6K citations

    16

    h-index

  4. Journal of Multivariate Analysis

    18 publications · 751 citations

    14

    h-index

  5. Journal of Statistical Planning and Inference

    21 publications · 617 citations

    14

    h-index

1–5