Pruning Timing

Pruning Timing is a structural optimization strategy in neural network training that specifies the point in the learning process at which weights or neurons are selectively removed to enhance model efficiency without compromising performance.

12

Publications

206

Citations

33

Authors

10

Institutions

Publications per year

2017–2026

4

Authors

33

  1. SS
    Sachin S. Sapatnekar

    University of Minnesota, United States

    2 publications · 28 citations

    2

    h-index

  2. HQ
    Haifeng Qian

    University of Minnesota, United States

    2 publications · 28 citations

    2

    h-index

  3. HM
    Hushrav Mogal

    University of Minnesota, United States

    2 publications · 28 citations

    2

    h-index

  4. KB
    Kia Bazargan

    University of Minnesota, United States

    2 publications · 28 citations

    2

    h-index

  5. AS
    Andrii Skliar

    Qualcomm (United Kingdom), United Kingdom

    1 publications · 17 citations

    1

    h-index

1–5 of 33

Venues

  1. Scientia Horticulturae

    1 publications · 27 citations

    1

    h-index

  2. 1

    h-index

  3. eCommons (Cornell University)

    Repository · 1 publications · 18 citations

    1

    h-index

  4. Ciência e Agrotecnologia

    1 publications · 16 citations

    1

    h-index

  5. Neurocomputing

    1 publications · 30 citations

    1

    h-index

1–5