A Concise Review of Recent Few-shot Meta-learning Methods
This is an incremental review paper summarizing existing methods for researchers in few-shot meta-learning.
The paper provides a concise review of recent few-shot meta-learning methods, categorizing them into four branches based on technical characteristics, and concludes with current challenges and future prospects.
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.