A machine learning model with human cognitive biases capable of learning from small and biased datasets

Abstract Human learners can generalize a new concept from a small number of samples. In contrast, conventional machine learning methods require large amounts of data to address the same types of problems. Humans have cognitive biases that promote fast learning. Here, we developed a method to reduce...

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Autores principales: Hidetaka Taniguchi, Hiroshi Sato, Tomohiro Shirakawa
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2018
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Acceso en línea:https://doaj.org/article/ce9a99c739bf4f4896c11549c24389ad
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