Strong Convexity

Strong Convexity is a property of a differentiable function in convex analysis where the function is uniformly bounded below by a quadratic function, ensuring a unique minimum and enhanced convergence properties in optimization.

2.6K

Publications

132.7K

Citations

3.4K

Authors

1.3K

Institutions

Publications per year

2017–2026

524

Authors

3.4K

  1. YC
    Yu‐Ming Chu

    Huzhou University, China

    31 publications · 1.4K citations

    24

    h-index

  2. JM
    Jonathan M. Borwein

    Dalhousie University, Canada

    31 publications · 2K citations

    23

    h-index

  3. SS
    Sever S Dragomir

    Victoria University, Australia

    29 publications · 1.1K citations

    18

    h-index

  4. RT
    R. T. Rockafellar

    University of Washington, United States

    16 publications · 2.3K citations

    16

    h-index

  5. ‎P
    ‎Josip Pečarić

    University of Zagreb, Croatia

    23 publications · 856 citations

    14

    h-index

1–5 of 3.4K

Venues

  1. arXiv (Cornell University)

    Repository · 187 publications · 9.3K citations

    45

    h-index

  2. Journal of Mathematical Analysis and Applications

    123 publications · 6.4K citations

    39

    h-index

  3. SIAM Journal on Optimization

    82 publications · 6K citations

    36

    h-index

  4. Mathematical Programming

    84 publications · 5.4K citations

    36

    h-index

  5. Journal of Optimization Theory and Applications

    111 publications · 4.1K citations

    34

    h-index

1–5