Local Metric Learning

Local Metric Learning is a metric learning approach that belongs to the class of distance metric learning methods, distinguished by its focus on learning distinct, localized distance metrics in different regions of the feature space to better capture fine-grained, context-specific similarity patterns.

121

Publications

23.3K

Citations

334

Authors

159

Institutions

Publications per year

2017–2026

43

Authors

334

  1. JL
    Jiwen Lu

    Tsinghua University, China

    8 publications · 684 citations

    8

    h-index

  2. HC
    Hong Chang

    Institute of Computing Technology, China

    5 publications · 233 citations

    5

    h-index

  3. JZ
    Jie Zhou

    Tsinghua University, China

    4 publications · 385 citations

    4

    h-index

  4. DG
    Dimitrios Gunopulos

    University of California, Riverside, United States

    4 publications · 411 citations

    4

    h-index

  5. CD
    Carlotta Domeniconi

    George Mason University, United States

    4 publications · 411 citations

    4

    h-index

1–5 of 334

Venues

  1. Pattern Recognition

    9 publications · 383 citations

    9

    h-index

  2. arXiv (Cornell University)

    Repository · 8 publications · 813 citations

    8

    h-index

  3. 7

    h-index

  4. 6

    h-index

  5. IEEE Transactions on Neural Networks

    3 publications · 324 citations

    3

    h-index

1–5