摘要
学习算法的可学习性是统计学习理论的基本问题.本文指出,一个随机学习问题具有可学习性当且仅当存在AERM且一致LOO稳定的学习规则.同时,得到随机学习规则下通用学习算法的一些结果.
The problem of learnability is one of the most basic questions in statistical learning theory.We show that a randomized learning problem is learnable if and only if there exists a learning rule which is always an AERM and uniform-LOO stable.Moreover,a generic learning algorithm in randomization learning rule setting will study.
出处
《苏州大学学报（自然科学版）》
CAS
2012年第4期30-35,共6页
Journal of Soochow University(Natural Science Edition)
基金
Supported by the National Natural Science Foundation of China(60903131)
Key Science and Technology Research Project of Education Ministry(210210)
关键词
统计学习理论
学习性
一致收敛
经验风险最小
稳定性
statistical learning theory
learnability
uniform convergence
empirical risk minimizer
stability
