Large-scale Classification

Large-Scale Classification is a machine learning task that involves assigning categorical labels to a vast number of instances or classes, distinguished by its computational and algorithmic challenges arising from the high dimensionality, massive volume, or both, of the data involved.

619

Publications

70.5K

Citations

2K

Authors

673

Institutions

Publications per year

2017–2026

314

Authors

2K

  1. YY
    Yiming Yang

    Carnegie Mellon University, United States

    9 publications · 1.5K citations

    9

    h-index

  2. CL
    Chih‐Jen Lin

    National Taiwan University, Taiwan

    7 publications · 7.2K citations

    7

    h-index

  3. RB
    Rohit Babbar

    Aalto University, Finland

    6 publications · 320 citations

    6

    h-index

  4. JF
    Jianping Fan

    University of North Carolina at Charlotte, United States

    6 publications · 190 citations

    6

    h-index

  5. ÉG
    Éric Gaussier

    Laboratoire d'Informatique de Grenoble, France

    6 publications · 268 citations

    6

    h-index

1–5 of 2K

Venues

  1. arXiv (Cornell University)

    Repository · 70 publications · 4.9K citations

    27

    h-index

  2. IEEE Access

    13 publications · 581 citations

    13

    h-index

  3. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 12 publications · 1.9K citations

    12

    h-index

  4. Neurocomputing

    12 publications · 1K citations

    12

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 8 publications · 260 citations

    8

    h-index

1–5