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### 谱机器学习研究综述

1. 苏州大学 计算机科学与技术学院，江苏 苏州 215000
• 出版日期:2015-12-01 发布日期:2015-12-04

### Survey on Spectral Machine Learning

YIN Hongwei, LI Fanzhang+

1. College of Computer Science and Technology, Soochow University, Suzhou, Jiangsu 215000, China
• Online:2015-12-01 Published:2015-12-04

Abstract: There are many problems in the fields of natural science which are difficult to be resolved due to continuous variation. These complex problems can be expressed as the combination of a series of simple problems which are distributed among the discrete spaces. The approximate solution of the complex problems can be obtained by solving the simple problems. In recent years, the spectral learning based on spectral mathematic theory is attracting more and more attention in machine learning. Compared with traditional learning methods, it can not only preserve the latent structure in the data, but also obtain a global optimization solution. This paper firstly introduces the basic theory of spectral learning, then shows some typical algorithms including spectral clustering, spectral learning of latent variable probabilistic model and spectral manifold learning, and finally presents some worthy perspectives according to the current researches.