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《Computer Engineering and Applications》 2010-15
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Contrasting research of global preserving manifold learning algorithms

ZENG Xian-hua1,LUO Si-wei21.Institute of Science & Technology of Computer,Chongqing University of Posts and Telecommunications,Chongqing 400065,China 2.School of Computer and Information Technology,Beijing Jiaotong University,Beijing 100044,China  
Global preserving manifold learning algorithms are mainly based on preserving global geometric properties between high-dimensional observed space and intrinsic low-dimensional manifold.This paper compares in detail the characters and interre-lations of several classical manifold learning algorithms based on preserving global properties.Some advantages and shortcomings of these algorithms are shown.Experimental results demonstrate the differences of these algorithms about intrinsic dimension and intrinsic low-dimensional manifold.Finally,several new research directions of manifold learning are proposed.
【Key Words】: global preserving spectral method kernel Principal Components Analysis ISOmetric MAPping Maximum Variance Unfolding
【Fund】: 国家自然科学基金No.60773016;; 重庆邮电大学博士启动基金项目(No.A2009-24)~~
【CateGory Index】: TP181
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