Heavy Pruning

Heavy Pruning is a pruning strategy within the field of model optimization that entails the aggressive removal of a substantial proportion of network weights or structural components, significantly reducing model size and complexity to enhance computational efficiency while risking diminished performance.

17

Publications

429

Citations

46

Authors

29

Institutions

Publications per year

2017–2026

2

Authors

46

  1. WJ
    William J. Rôbbins

    New York Botanical Garden, United States

    2 publications · 51 citations

    2

    h-index

  2. DR
    D.C. Ramsdell

    Michigan State University, United States

    2 publications · 33 citations

    2

    h-index

  3. GR
    Gary R. VanEe

    Michigan State University, United States

    2 publications · 33 citations

    2

    h-index

  4. RL
    Richard L. Ledebuhr

    Michigan State University, United States

    2 publications · 33 citations

    2

    h-index

  5. EH
    Eric Hanson

    Michigan State University, United States

    2 publications · 33 citations

    2

    h-index

1–5 of 46

Venues

  1. HortScience

    2 publications · 38 citations

    2

    h-index

  2. American Journal of Botany

    2 publications · 51 citations

    2

    h-index

  3. 2

    h-index

  4. Journal of Applied Entomology

    1 publications · 14 citations

    1

    h-index

  5. HortTechnology

    1 publications · 16 citations

    1

    h-index

1–5