Nonconvex Optimization

Nonconvex Optimization is a subfield of mathematical optimization that focuses on minimizing or maximizing nonlinear objective functions over feasible sets that lack convexity, thereby allowing for the existence of multiple local optima that are not necessarily global optima.

4.2K

Publications

279.5K

Citations

7.6K

Authors

1.8K

Institutions

Publications per year

2017–2026

2K

Authors

7.6K

  1. HD
    Hoang Duong Tuan

    University of Technology Sydney, Australia

    33 publications · 2.1K citations

    24

    h-index

  2. MH
    Mingyi Hong

    University of Minnesota, United States

    28 publications · 4K citations

    23

    h-index

  3. GS
    Gesualdo Scutari

    Sapienza University of Rome, Italy

    34 publications · 3.4K citations

    23

    h-index

  4. HV
    H. Vincent Poor

    Princeton University, United States

    30 publications · 2.5K citations

    21

    h-index

  5. XC
    Xiaojun Chen

    Hong Kong Polytechnic University, Hong Kong SAR China

    23 publications · 1.8K citations

    19

    h-index

1–5 of 7.6K

Venues

  1. IEEE Transactions on Signal Processing

    151 publications · 16.6K citations

    63

    h-index

  2. SIAM Journal on Optimization

    162 publications · 15.7K citations

    62

    h-index

  3. arXiv (Cornell University)

    Repository · 348 publications · 14.4K citations

    55

    h-index

  4. IEEE Internet of Things Journal

    102 publications · 8.7K citations

    51

    h-index

  5. Mathematical Programming

    91 publications · 13.9K citations

    48

    h-index

1–5