Self-incremental learning vector quantization with human cognitive biases

Abstract 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 (L...

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Autores principales: Nobuhito Manome, Shuji Shinohara, Tatsuji Takahashi, Yu Chen, Ung-il Chung
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/217e4b2b43ed42cc944849d1cacb86f7
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