Alternating Minimization

Alternating Minimization is an iterative optimization method that belongs to the class of coordinate descent algorithms, distinguished by its sequential minimization of the objective function with respect to subsets of variables while holding the remaining variables fixed.

295

Publications

24.5K

Citations

778

Authors

373

Institutions

Publications per year

2017–2026

133

Authors

778

  1. XY
    Xianghao Yu

    Hong Kong University of Science and Technology, Hong Kong SAR China

    6 publications · 308 citations

    6

    h-index

  2. MK
    Michael K. Ng

    Hong Kong Baptist University, Hong Kong SAR China

    5 publications · 230 citations

    5

    h-index

  3. SS
    Sujay Sanghavi

    The University of Texas at Austin, United States

    5 publications · 1.1K citations

    5

    h-index

  4. YL
    Youzuo Lin

    Los Alamos National Laboratory, United States

    4 publications · 227 citations

    4

    h-index

  5. SS
    Shoham Sabach

    Technion – Israel Institute of Technology, Israel

    4 publications · 156 citations

    4

    h-index

1–5 of 778

Venues

  1. arXiv (Cornell University)

    Repository · 26 publications · 898 citations

    16

    h-index

  2. IEEE Transactions on Signal Processing

    15 publications · 1K citations

    15

    h-index

  3. IEEE Transactions on Image Processing

    11 publications · 933 citations

    11

    h-index

  4. SIAM Journal on Imaging Sciences

    SIIMS · 8 publications · 3.1K citations

    8

    h-index

  5. Computational Optimization and Applications

    5 publications · 142 citations

    5

    h-index

1–5