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
Parents
539
On the Asymptotic Accuracy of Efron's Bootstrap
Kesar Singh · The Annals of Statistics · 1981 · 770 citations · Full text
A Note on Quantiles in Large Samples
R. R. Bahadur · The Annals of Mathematical Statistics · 1966 · 739 citations · Full text
1–5 of 539
991
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Hong Kong University of Science and Technology, Hong Kong SAR China
8 publications · 507 citations
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7
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6
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6
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1–5 of 991
560

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
10 h-index
20 publications
1.3K citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
8 h-index
13 publications
1.3K citations
Rutgers, The State University of New Jersey
New Brunswick, United States
7 h-index
8 publications
570 citations

Hefei University of Technology
Hefei, China
7 h-index
17 publications
670 citations
University of California, Los Angeles
Los Angeles, United States
7 h-index
10 publications
658 citations

Centre National de la Recherche Scientifique
Paris, France
7 h-index
10 publications
175 citations

Cochin University of Science and Technology
Ernakulam, India
7 h-index
19 publications
652 citations
Tsinghua University
Beijing, China
7 h-index
8 publications
437 citations
1–8 of 560
27 publications · 701 citations
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CSDA · 20 publications · 515 citations
16
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18 publications · 2.6K citations
16
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18 publications · 751 citations
14
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21 publications · 617 citations
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