Large-scale Sparse Optimization

Large-Scale Sparse Optimization is a mathematical optimization paradigm characterized by the minimization of objective functions involving a large number of variables or constraints with an inherent sparsity structure, where the majority of variables or coefficients are zero, enabling scalable and efficient computational solutions.

185

Publications

26.6K

Citations

422

Authors

246

Institutions

Publications per year

2017–2026

70

Authors

422

  1. XZ
    Xingyi Zhang

    Anhui University, China

    8 publications · 1K citations

    8

    h-index

  2. FF
    Francisco Facchinei

    Sapienza University of Rome, Italy

    6 publications · 379 citations

    6

    h-index

  3. GS
    Gesualdo Scutari

    Sapienza University of Rome, Italy

    6 publications · 379 citations

    6

    h-index

  4. YT
    Ye Tian

    Anhui University, China

    6 publications · 951 citations

    6

    h-index

  5. JN
    Julie Nutini

    University of British Columbia, Canada

    4 publications · 190 citations

    4

    h-index

1–5 of 422

Venues

  1. arXiv (Cornell University)

    Repository · 14 publications · 405 citations

    11

    h-index

  2. SIAM Journal on Optimization

    11 publications · 1.7K citations

    11

    h-index

  3. Mathematical Programming

    10 publications · 1.4K citations

    10

    h-index

  4. Optimization methods & software

    6 publications · 7.9K citations

    6

    h-index

  5. Swarm and Evolutionary Computation

    6 publications · 263 citations

    6

    h-index

1–5