元学习(计算机科学)
计算机科学
人工智能
机器学习
基于实例的学习
主动学习(机器学习)
学习分类器系统
领域(数学)
机器人学习
无监督学习
多任务学习
算法
任务(项目管理)
数学
工程类
机器人
系统工程
移动机器人
纯数学
作者
Madhava Gaikwad,Ashwini Doke
标识
DOI:10.1109/iciccs53718.2022.9788260
摘要
In Meta learning auto learning algorithms are applied to machine learning experiments. The Meta learning is trying to solve problem of learning to learn as there is a significant lack in data as well as experts. There are many novel approaches developed in field of meta learning in past few years. This paper is summary of ongoing research in field of meta learning. It describes current trends and development in field of meta learning and with tactic knowledge how the meta learning can be applied to achieve few shot learning. It is believe that the Meta learning will perform well to overcome the challenges of few shot learning.
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