Vector Clustering

Vector Clustering is a computational method that partitions a set of vectors in a high-dimensional space into groups based on their geometric similarity, distinguishing itself from other clustering techniques by explicitly leveraging vector representations and distance metrics inherent to vector spaces.

62

Publications

4.5K

Citations

161

Authors

58

Institutions

Publications per year

2017–2026

15

Authors

161

  1. AV
    A. V. Kel’manov

    Sobolev Institute of Mathematics, Russia

    3 publications · 61 citations

    3

    h-index

  2. LH
    Lucas Hosseini

    Université Paris Sciences et Lettres, France

    2 publications · 374 citations

    2

    h-index

  3. GS
    Gergely Szilvasy

    Zillow Group (United States), United States

    2 publications · 374 citations

    2

    h-index

  4. DM
    Daniel Müllner

    Stanford University, United States

    2 publications · 994 citations

    2

    h-index

  5. LB
    Lukáš Burget

    Brno University of Technology, Czechia

    2 publications · 86 citations

    2

    h-index

1–5 of 161

Venues

  1. arXiv (Cornell University)

    Repository · 7 publications · 515 citations

    7

    h-index

  2. Expert Systems with Applications

    2 publications · 137 citations

    2

    h-index

  3. Journal of Applied and Industrial Mathematics

    2 publications · 40 citations

    2

    h-index

  4. Pattern Recognition

    2 publications · 75 citations

    2

    h-index

  5. IFAC-PapersOnLine

    1 publications · 15 citations

    1

    h-index

1–5