节点文献

基于Lie群的机器学习理论框架

The study of machine learning theory frame based on Lie group

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 李凡长康宇

【Author】 LI Fan-zhang,KANG Yu(School of Computer Science & Technology, Soochow University, Suzhou 2150006,China)

【机构】 苏州大学计算机科学与技术学院苏州大学计算机科学与技术学院 浙江苏州 215006浙江苏州 215006

【摘要】 借用具有良好数学结构的Lie群来研究机器学习,提出了基于Lie群的机器学习(ML)基本概念、对偶空间学习概念等,形成了基于Lie群的学习理论框架.该理论框架可以用代数和几何的方法来描述机器学习系统,弥补了原有机器学习理论的不足.

【Abstract】 Machine learning is a eternal problem in the researches of artificial intelligence. However, machine learning methods are short of systemic theoretic foundation at present and some preferable ones such as statistic learning theory are exploring ones. Therefore, this paper researches machine learning by Lie group which has good mathematics configuration advances some basic conceptions of machine learning (ML) based on Lie group and conceptions of learning based on dual space, and formed the basic learning theory frame based on Lie group. The theory frame can describe machine learning system by algebra and geometry methods. So that it makes a fine configuration for describing the procession of machine learning and makes up for the lack of other theories of machine learning. It can be believed that researches of machine learning could be profoundly influenced by these works.

【关键词】 李群机器学习李代数对偶空间
【Key words】 lie groupmachine leaninglie algebradual space
【基金】 江苏省自然科学基金(BK2002040);江苏省教育厅自然科学基金(03KJB520128).
  • 【文献出处】 云南民族大学学报(自然科学版) ,Journal of Yunnan University for Nationalites(Natral Sciences Edition) , 编辑部邮箱 ,2004年04期
  • 【分类号】TP181
  • 【被引频次】13
  • 【下载频次】291
节点文献中: 

本文链接的文献网络图示:

本文的引文网络