Nonsmooth Convex Optimization

Nonsmooth Convex Optimization is a subfield of convex optimization characterized by the minimization of convex functions that are not necessarily differentiable, where the lack of smoothness necessitates specialized algorithms such as subgradient, proximal, or bundle methods to handle non-differentiable points in the objective function.

987

Publications

60.6K

Citations

1.5K

Authors

697

Institutions

Publications per year

2017–2026

302

Authors

1.5K

  1. AB
    Adil Bagirov

    Federation University, Australia

    19 publications · 921 citations

    16

    h-index

  2. KC
    Krzysztof C. Kiwiel

    Systems Research Institute, Poland

    13 publications · 1.1K citations

    13

    h-index

  3. XC
    Xiaojun Chen

    Hong Kong Polytechnic University, Hong Kong SAR China

    13 publications · 795 citations

    13

    h-index

  4. MM
    Marko M. Mäkelä

    University of Turku, Finland

    13 publications · 678 citations

    13

    h-index

  5. WB
    Wei Bian

    Harbin Institute of Technology, China

    13 publications · 854 citations

    13

    h-index

1–5 of 1.5K

Venues

  1. SIAM Journal on Optimization

    97 publications · 8.2K citations

    48

    h-index

  2. Mathematical Programming

    85 publications · 7.7K citations

    46

    h-index

  3. Journal of Optimization Theory and Applications

    92 publications · 6.2K citations

    34

    h-index

  4. arXiv (Cornell University)

    Repository · 61 publications · 2.3K citations

    22

    h-index

  5. Journal of Global Optimization

    34 publications · 1.6K citations

    21

    h-index

1–5