统计学习理论基础研究新进展

New Progress in Basic Research of Statistical Learning Theory

统计学习理论是研究小样本情况下机器学习的理论。在该理论基础上发展起来的支持向量机在许多方面都有应用。系统地整理分析了统计学习理论基础研究的文献,将其主要划分为概率空间的扩展,随机样本的变化,以及两者相结合三个方面介绍了统计学习理论基础研究的新进展,并对未来的发展进行了展望。

Statistical learning theory is the study of small sample situation of machine learning theory. Support vector machine（SVM） is developed on the basis of this theory and it is used in many ways. Basic research literature of statistical learning theory is systematically sorted out and analyzed,which is mainly divided into three aspects, the expansion of the probability space, random sample variation, and the combination of space and sample. This paper introduces the research progress of statistical learning theory foundation, and the future development is prospected.