Concepedia

Pruning Compression Trade-offs

Pruning Compression Trade-Offs is a theoretical framework in machine learning that characterizes the inherent balance between model compression efficiency and performance degradation resulting from selective removal of network parameters.

117

Publications

10.7K

Citations

425

Authors

152

Institutions

Publications per year

2017–2026

111

Parents

Publications

117

ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression

Jian-Hao Luo, Jianxin Wu, Weiyao Lin · 2017 · 2K citations

, , +15

Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration

Yang He, Ping Liu, Ziwei Wang et al. · 2019 · 1.2K citations · Full text

, , +16

To prune, or not to prune: exploring the efficacy of pruning for model compression

Michael Zhu, Suyog Gupta · arXiv (Cornell University) · 2017 · 663 citations · Full text

, , +16

The State of Sparsity in Deep Neural Networks

Trevor Gale, Erich Elsen, Sara Hooker · arXiv (Cornell University) · 2019 · 441 citations · Full text

, , +16

On Compressing Deep Models by Low Rank and Sparse Decomposition

Xiyu Yu, Tongliang Liu, Xinchao Wang et al. · 2017 · 428 citations

, , +16

1–5 of 117

Authors

425

  1. JL
    Jian-Hao Luo

    Nanjing University, China

    6 publications · 2.6K citations

    6

    h-index

  2. JW
    Jianxin Wu

    Nanjing University, China

    6 publications · 2.6K citations

    6

    h-index

  3. GM
    Greg Mori

    Simon Fraser University, Canada

    4 publications · 403 citations

    4

    h-index

  4. FT
    Frederick Tung

    University of British Columbia, Canada

    4 publications · 403 citations

    4

    h-index

  5. YW
    Yanzhi Wang

    Northeastern University, United States

    4 publications · 101 citations

    4

    h-index

1–5 of 425

Institutions

152

  1. Nanjing University

    Nanjing, China

    6 h-index

    14 publications

    5.6K citations

  2. Shanghai Jiao Tong University

    Shanghai, China

    5 h-index

    10 publications

    2.5K citations

  3. Tsinghua University

    Beijing, China

    4 h-index

    8 publications

    480 citations

  4. Princeton University

    Princeton, United States

    4 h-index

    7 publications

    506 citations

  5. Peking University

    Beijing, China

    4 h-index

    5 publications

    183 citations

  6. Simon Fraser University

    Burnaby, Canada

    3 h-index

    7 publications

    796 citations

  7. Southern University of Science and Technology

    Shenzhen, China

    3 h-index

    5 publications

    136 citations

  8. University of Science and Technology of China

    Hefei, China

    3 h-index

    8 publications

    833 citations

1–8 of 152

Venues

  1. arXiv (Cornell University)

    Repository · 34 publications · 2.6K citations

    22

    h-index

  2. IEEE Access

    5 publications · 477 citations

    5

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 4 publications · 111 citations

    4

    h-index

  4. Applied Sciences

    2 publications · 50 citations

    2

    h-index

  5. 2

    h-index

1–5