Weight Sparsity

Weight Sparsity is a structural efficiency metric in neural network pruning that quantifies the proportion of zero-valued weights relative to the total number of weights in a model, serving as a measure of model compactness.

70

Publications

3.2K

Citations

297

Authors

101

Institutions

Publications per year

2017–2026

61

Authors

297

  1. YW
    Yanzhi Wang

    Northeastern University, United States

    6 publications · 192 citations

    6

    h-index

  2. SK
    Sanghoon Kang

    Korea Advanced Institute of Science and Technology, South Korea

    3 publications · 60 citations

    3

    h-index

  3. JL
    Juhyoung Lee

    Korea Advanced Institute of Science and Technology, South Korea

    3 publications · 60 citations

    3

    h-index

  4. HY
    Hoi‐Jun Yoo

    Korea Advanced Institute of Science and Technology, South Korea

    3 publications · 60 citations

    3

    h-index

  5. XL
    Xue Lin

    Northeastern University, United States

    3 publications · 96 citations

    3

    h-index

1–5 of 297

Venues

  1. arXiv (Cornell University)

    Repository · 13 publications · 590 citations

    13

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  2. 3

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  3. 3

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  4. 2

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  5. 2

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1–5