Light Pruning

Light Pruning is a pruning strategy in machine learning that removes a relatively small proportion of model parameters or connections, typically preserving the majority of the original network structure while aiming to maintain model performance with minor reductions in complexity.

7

Publications

148

Citations

22

Authors

8

Institutions

Publications per year

2017–2026

1

Authors

22

  1. CO
    Carmen Olmo

    Universitat de València, Spain

    1 publications · 10 citations

    1

    h-index

  2. RS
    Robert S. Rogers

    University of Missouri, United States

    1 publications · 17 citations

    1

    h-index

  3. DH
    D. H. Lambert

    University of Maine, United States

    1 publications · 24 citations

    1

    h-index

  4. PS
    Peter Spathelf

    Eberswalde University for Sustainable Development, Germany

    1 publications · 17 citations

    1

    h-index

  5. AM
    Anber M. A. Hassanein

    Sohag University, Egypt

    1 publications · 24 citations

    1

    h-index

1–5 of 22

Venues

  1. Annals of Forest Science

    1 publications · 17 citations

    1

    h-index

  2. Applied Soft Computing

    1 publications · 31 citations

    1

    h-index

  3. 1

    h-index

  4. OENO One

    1 publications · 10 citations

    1

    h-index

  5. Plant Disease

    1 publications · 24 citations

    1

    h-index

1–5