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 |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/217e4b2b43ed42cc944849d1cacb86f7 |
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