Crossed Features

Crossed Features is a methodological construct in machine learning that combines two or more distinct feature dimensions through Cartesian product expansion to generate higher-order interaction representations.

29

Publications

2.4K

Citations

105

Authors

46

Institutions

Publications per year

2017–2026

14

Variants

Feature Crosses

Authors

105

  1. RW
    Ruoxi Wang

    Fiberhome Technology Group (China), China

    3 publications · 1.2K citations

    3

    h-index

  2. GF
    Gang Fu

    Wuhan University, China

    2 publications · 1.2K citations

    2

    h-index

  3. WC
    Weiyu Cheng

    Shanghai Jiao Tong University, China

    2 publications · 177 citations

    2

    h-index

  4. LH
    Linpeng Huang

    Shanghai Jiao Tong University, China

    2 publications · 177 citations

    2

    h-index

  5. BF
    Bin Fu

    Hunan University, China

    2 publications · 1.2K citations

    2

    h-index

1–5 of 105

Venues

  1. arXiv (Cornell University)

    Repository · 3 publications · 68 citations

    3

    h-index

  2. Forensic Science International

    1 publications · 26 citations

    1

    h-index

  3. FEBS Journal

    1 publications · 15 citations

    1

    h-index

  4. Perceptual and Motor Skills

    1 publications · 36 citations

    1

    h-index

  5. SubStance

    1 publications · 13 citations

    1

    h-index

1–5