Self-incremental learning vector quantization with human cognitive biases

Human beings have adaptively rational cognitive biases for efficiently acquiring concepts from small-sized datasets. With such inductive biases, humans can generalize concepts by learning a small number of samples. By incorporating human cognitive biases into learning vector quantization (LVQ), a pr...

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Detalles Bibliográficos
Autores principales: Manome, Nobuhito, Shinohara, Shuji, Takahashi, Tatsuji, Chen, Yu, Chung, Ung-il
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7887244/
https://www.ncbi.nlm.nih.gov/pubmed/33594132
http://dx.doi.org/10.1038/s41598-021-83182-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7887244/
https://www.ncbi.nlm.nih.gov/pubmed/33594132
http://dx.doi.org/10.1038/s41598-021-83182-4

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