Label Spreading

Label Spreading is a semi-supervised learning algorithm that belongs to the family of graph-based methods, distinguished by its propagation of label information across data points through a harmonic function on a weighted graph, where the weights reflect pairwise similarities among instances.

28

Publications

1.4K

Citations

90

Authors

48

Institutions

Publications per year

2017–2026

13

Authors

90

  1. LZ
    Liang Zhao

    Universidade de São Paulo, Brazil

    3 publications · 151 citations

    3

    h-index

  2. AD
    Alneu de Andrade Lopes

    Universidade de São Paulo, Brazil

    2 publications · 44 citations

    2

    h-index

  3. XZ
    Xiankun Zhang

    University of Science and Technology Beijing, China

    2 publications · 43 citations

    2

    h-index

  4. AS
    Amanda S. Barnard

    Commonwealth Scientific and Industrial Research Organisation, Australia

    2 publications · 81 citations

    2

    h-index

  5. CS
    Chen Song

    Tianjin University of Science and Technology, China

    2 publications · 43 citations

    2

    h-index

1–5 of 90

Venues

  1. International Journal of Modern Physics B

    2 publications · 43 citations

    2

    h-index

  2. 2

    h-index

  3. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 2 publications · 125 citations

    2

    h-index

  4. Knowledge-Based Systems

    1 publications · 71 citations

    1

    h-index

  5. Royal Society Open Science

    1 publications · 29 citations

    1

    h-index

1–5