Adaptive Complexity

Adaptive Complexity is a theoretical construct in algorithm analysis that characterizes the efficiency of a sorting algorithm by its ability to exploit existing order in the input sequence, thereby reducing computational effort relative to worst-case complexity when processing partially sorted data.

47

Publications

6.3K

Citations

97

Authors

58

Institutions

Publications per year

2017–2026

13

Authors

97

  1. MS
    Muhammad Shafique

    Karlsruhe Institute of Technology, Germany

    3 publications · 135 citations

    3

    h-index

  2. YS
    Yaron Singer

    Harvard University Press, United States

    3 publications · 136 citations

    3

    h-index

  3. EB
    Eric Balkanski

    Harvard University Press, United States

    3 publications · 136 citations

    3

    h-index

  4. LU
    Lyle Ungar

    University of Pennsylvania, United States

    3 publications · 242 citations

    3

    h-index

  5. DP
    Dean P. Foster

    University of Pennsylvania, United States

    3 publications · 242 citations

    3

    h-index

1–5 of 97

Venues

  1. Artificial Life

    2 publications · 783 citations

    2

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  2. Biology & Philosophy

    2 publications · 55 citations

    2

    h-index

  3. Journal of Management Development

    JMD · 1 publications · 15 citations

    1

    h-index

  4. American Psychologist

    1 publications · 279 citations

    1

    h-index

  5. 1

    h-index

1–5