Machine Learning In Performance

Machine Learning in Performance is a scholarly contribution that integrates machine learning techniques into the analysis, optimization, or evaluation of algorithmic performance, distinguished by its focus on adaptive, data-driven models to enhance or understand computational efficiency, accuracy, or scalability within specific performance domains.

7

Publications

449

Citations

25

Authors

13

Institutions

Publications per year

2017–2026

5

Authors

25

  1. SH
    Shibani Hawladar

    Gujarat Technological University, India

    1 publications · 114 citations

    1

    h-index

  2. MH
    Mat Herold

    Bundesdruckerei (Germany), Germany

    1 publications · 131 citations

    1

    h-index

  3. SK
    Selvi Kadirvel

    University of Florida, United States

    1 publications · 32 citations

    1

    h-index

  4. DS
    Darko Stefanović

    University of Novi Sad, Serbia

    1 publications · 17 citations

    1

    h-index

  5. CT
    Chris Thompson

    Saarland University, Germany

    1 publications · 131 citations

    1

    h-index

1–5 of 25

Venues

  1. Materials Today Proceedings

    1 publications · 114 citations

    1

    h-index

  2. International Journal of Architectural Computing

    IJAC · 1 publications · 90 citations

    1

    h-index

  3. Sustainability

    1 publications · 53 citations

    1

    h-index

  4. 1

    h-index

  5. Journal of Sports Sciences

    1 publications · 11 citations

1–5