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A Concise Review of Recent Few-shot Meta-learning Methods

2020-05-22 00:39:14
Xiaoxu Li, Zhuo Sun, Jing-Hao Xue, Zhanyu Ma
arXiv_CV
       
Abstract

Few-shot meta-learning has been recently reviving with expectations to mimic humanity's fast adaption to new concepts based on prior knowledge. In this short communication, we give a concise review on recent representative methods in few-shot meta-learning, which are categorized into four branches according to their technical characteristics. We conclude this review with some vital current challenges and future prospects in few-shot meta-learning.

Abstract (translated)

URL

https://arxiv.org/abs/2005.10953

PDF

https://arxiv.org/pdf/2005.10953.pdf

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