Feature Hashing

Feature Hashing is a dimensionality reduction technique in domain-specific feature design that maps high-cardinality categorical features into a fixed-size vector space using a hash function, thereby enabling efficient feature transformation while preserving computational scalability.

175

Publications

11.9K

Citations

567

Authors

229

Institutions

Publications per year

2017–2026

97

Authors

567

  1. ZT
    Zhenjun Tang

    Guangxi Normal University, China

    7 publications · 481 citations

    7

    h-index

  2. XZ
    Xianquan Zhang

    Guangxi Normal University, China

    6 publications · 448 citations

    6

    h-index

  3. JH
    Junfeng He

    Columbia University, United States

    5 publications · 452 citations

    5

    h-index

  4. XL
    Xianglong Liu

    Beihang University, China

    5 publications · 331 citations

    5

    h-index

  5. KQ
    Kilian Q. Weinberger

    Cornell University, United States

    4 publications · 1.2K citations

    4

    h-index

1–5 of 567

Venues

  1. arXiv (Cornell University)

    Repository · 10 publications · 203 citations

    10

    h-index

  2. IEEE Transactions on Image Processing

    7 publications · 606 citations

    7

    h-index

  3. Neurocomputing

    4 publications · 135 citations

    5

    h-index

  4. IEEE Transactions on Multimedia

    5 publications · 532 citations

    5

    h-index

  5. Multimedia Tools and Applications

    5 publications · 118 citations

    5

    h-index

1–5