Temporal Matrix Factorization

Temporal Matrix Factorization is a matrix factorization method that incorporates temporal dynamics by modeling time-evolving latent factors to capture sequential or time-dependent patterns in data.

49

Publications

2.2K

Citations

175

Authors

93

Institutions

Publications per year

2017–2026

30

Authors

175

  1. UK
    U Kang

    Seoul National University, South Korea

    2 publications · 44 citations

    3

    h-index

  2. NR
    Nikhil Rao

    University of Wisconsin–Madison, United States

    2 publications · 341 citations

    2

    h-index

  3. JJ
    Jun-Gi Jang

    Seoul National University, South Korea

    1 publications · 24 citations

    2

    h-index

  4. IS
    Inderjit S. Dhillon

    The University of Texas at Austin, United States

    2 publications · 341 citations

    2

    h-index

  5. HY
    Hsiang‐Fu Yu

    The University of Texas at Austin, United States

    2 publications · 341 citations

    2

    h-index

1–5 of 175

Venues

  1. Expert Systems with Applications

    2 publications · 83 citations

    3

    h-index

  2. IEEE Access

    3 publications · 46 citations

    3

    h-index

  3. Neurocomputing

    2 publications · 51 citations

    2

    h-index

  4. 2

    h-index

  5. Information Sciences

    2 publications · 39 citations

    2

    h-index

1–5