Convex Network Optimization

Convex Network Optimization is a network optimization framework in which the objective function and all constraint functions are convex, ensuring that any local minimum is a global minimum and enabling efficient solution via convex optimization techniques.

128

Publications

6.1K

Citations

337

Authors

165

Institutions

Publications per year

2017–2026

39

Authors

337

  1. SH
    Steven H. Low

    California Institute of Technology, United States

    7 publications · 601 citations

    7

    h-index

  2. DP
    Dimitri P. Bertsekas

    Massachusetts Institute of Technology, United States

    5 publications · 291 citations

    5

    h-index

  3. AN
    Angelia Nedić

    University of Illinois Urbana-Champaign, United States

    4 publications · 521 citations

    4

    h-index

  4. AR
    Alejandro Ribeiro

    University of Pennsylvania, United States

    4 publications · 397 citations

    4

    h-index

  5. WS
    Wei Shi

    Arizona State University, United States

    3 publications · 478 citations

    3

    h-index

1–5 of 337

Venues

  1. IEEE Transactions on Automatic Control

    5 publications · 876 citations

    5

    h-index

  2. IEEE Transactions on Signal Processing

    5 publications · 409 citations

    5

    h-index

  3. IEEE Access

    4 publications · 105 citations

    4

    h-index

  4. arXiv (Cornell University)

    Repository · 4 publications · 138 citations

    4

    h-index

  5. IEEE Transactions on Vehicular Technology

    5 publications · 147 citations

    4

    h-index

1–5