Dimension Reduction

Dimension Reduction is a statistical technique that belongs to the class of methods for transforming high-dimensional data into a lower-dimensional space while preserving essential structure or variation, thereby facilitating interpretation, visualization, and computational efficiency.

12K

Publications

967.3K

Citations

23K

Authors

4.3K

Institutions

Publications per year

2017–2026

3.9K

Authors

23K

  1. FN
    Feiping Nie

    Northwestern Polytechnical University, China

    116 publications · 7.7K citations

    49

    h-index

  2. DT
    Dacheng Tao

    The University of Sydney, Australia

    55 publications · 6.3K citations

    37

    h-index

  3. SY
    Shuicheng Yan

    National University of Singapore, Singapore

    55 publications · 11.2K citations

    35

    h-index

  4. RD
    R. Dennis Cook

    University of Minnesota, United States

    46 publications · 4.6K citations

    34

    h-index

  5. XL
    Xuelong Li

    Xi'an Institute of Optics and Precision Mechanics, China

    38 publications · 5K citations

    32

    h-index

1–5 of 23K

Venues

  1. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 165 publications · 33K citations

    78

    h-index

  2. Journal of the American Statistical Association

    156 publications · 24.8K citations

    70

    h-index

  3. Pattern Recognition

    214 publications · 18K citations

    68

    h-index

  4. arXiv (Cornell University)

    Repository · 497 publications · 31.8K citations

    65

    h-index

  5. IEEE Transactions on Image Processing

    141 publications · 13.5K citations

    64

    h-index

1–5