Similarity-based Learning

Similarity-Based Learning is a cognitive learning paradigm within concept formation that categorizes instances based on shared perceptual or structural features, distinguishing itself by relying on similarity relations among stimuli rather than explicit rule-based or feedback-driven mechanisms.

474

Publications

25.5K

Citations

1.3K

Authors

565

Institutions

Publications per year

2017–2026

218

Authors

1.3K

  1. AV
    Anna V. Fisher

    Carnegie Mellon University, United States

    6 publications · 727 citations

    6

    h-index

  2. WD
    Walter Daelemans

    University of Antwerp, Belgium

    6 publications · 259 citations

    6

    h-index

  3. LC
    Longbing Cao

    University of Technology Sydney, Australia

    5 publications · 179 citations

    5

    h-index

  4. MR
    Maya R. Gupta

    University of Washington, United States

    5 publications · 437 citations

    5

    h-index

  5. VM
    Vladimir M. Sloutsky

    The Ohio State University, United States

    5 publications · 691 citations

    5

    h-index

1–5 of 1.3K

Venues

  1. arXiv (Cornell University)

    Repository · 20 publications · 358 citations

    13

    h-index

  2. IEEE Access

    11 publications · 556 citations

    11

    h-index

  3. Journal of Experimental Psychology

    7 publications · 359 citations

    7

    h-index

  4. Cognitive Science

    7 publications · 120 citations

    7

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 6 publications · 210 citations

    6

    h-index

1–5