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Context sequence theory: a common explanation for multiple types of learning

2022/07/17 by Mingcan Yu, Mingcan, Yu, Junying, Wang
Biochemistry, Genetics and Molecular Biology · Computer Science · #Machine Learning in Bioinformatics #Neural Networks and Applications

paper · pdf · doi:10.48550/arxiv.2208.04707

Abstract

Although principles of neuroscience like reinforcement learning, visual perception and attention have been applied in machine learning models, there is a huge gap between machine learning and mammalian learning. Based on the advances in neuroscience, we propose the context sequence theory to give a common explanation for multiple types of learning in mammals and hope that can provide a new insight into the construct of machine learning models.

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