Sparse Models

Sparse Models is a class of statistical models characterized by the deliberate restriction of model parameters to contain a significant number of zero values, thereby enhancing interpretability and computational efficiency in high-dimensional data settings.

1.2K

Publications

98.9K

Citations

3.1K

Authors

1K

Institutions

Publications per year

2017–2026

475

Variants

Sparsity-based Models

Authors

3.1K

  1. VC
    Victor Chernozhukov

    Massachusetts Institute of Technology, United States

    19 publications · 2.9K citations

    17

    h-index

  2. AB
    Alexandre Belloni

    Duke University, United States

    16 publications · 2.6K citations

    16

    h-index

  3. GS
    Guillermo Sapiro

    University of Minnesota, United States

    15 publications · 3.8K citations

    14

    h-index

  4. JF
    Jianqing Fan

    Princeton University, United States

    11 publications · 1.5K citations

    11

    h-index

  5. SC
    Sheng Chen

    University of Southampton, United Kingdom

    8 publications · 487 citations

    8

    h-index

1–5 of 3.1K

Venues

  1. arXiv (Cornell University)

    Repository · 114 publications · 6.4K citations

    34

    h-index

  2. The Annals of Statistics

    39 publications · 4.9K citations

    29

    h-index

  3. Journal of the American Statistical Association

    24 publications · 3.8K citations

    19

    h-index

  4. Electronic Journal of Statistics

    20 publications · 751 citations

    16

    h-index

  5. IEEE Transactions on Signal Processing

    15 publications · 1.1K citations

    14

    h-index

1–5