Yuncong Peng1,2, Xiaolin Qin1,2,*, Qianlei Wang1,2, Boyi Fu1,2, Yongxiang Gu1,2
Computer Systems Science and Engineering, Vol.46, No.1, pp. 1233-1247, 2023, DOI:10.32604/csse.2023.032633
Abstract At present, deep learning has been well applied in many fields. However, due to the high complexity of hypothesis space, numerous training samples are usually required to ensure the reliability of minimizing experience risk. Therefore, training a classifier with a small number of training examples is a challenging task. From a biological point of view, based on the assumption that rich prior knowledge and analogical association should enable human beings to quickly distinguish novel things from a few or even one example, we proposed a dynamic analogical association algorithm to make the model use only a few labeled samples for… More >
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