[1]徐 蓉,姜 峰,姚鸿勋.流形学习概述[J].智能系统学报,2006,1(1):44-51.
XU Rong,JIANG Feng,YAO Hong-xun.Overview of manifold learning[J].CAAI Transactions on Intelligent Systems,2006,1(1):44-51.
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XU Rong,JIANG Feng,YAO Hong-xun.Overview of manifold learning[J].CAAI Transactions on Intelligent Systems,2006,1(1):44-51.
流形学习概述
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
1
期数:
2006年第1期
页码:
44-51
栏目:
综述
出版日期:
2006-03-25
- Title:
- Overview of manifold learning
- 文章编号:
- 1673-4785(2006)01-0044-08
- Keywords:
- dimensionality reduction; manifold learning; Isomap; LLE; intersectin g manifold
- 分类号:
- TP181
- 文献标志码:
- A
- 摘要:
- 流形学习是一种新的非监督学习方法，近年来引起越来越多机器学习和认知科学工作者的重视.为了加深对流形学习的认识和理解，该文由流形学习的拓扑学概念入手，追溯它的发展过程.在明确流形学习的不同表示方法后，针对几种主要的流形算法，分析它们各自的优势和不足，然后分别引用Isomap和LLE的应用示例.结果表明，流形学习较之于传统的线性降维方法，能够有效地发现非线性高维数据的本质维数，利于进行维数约简和数据分析.最后对流形学习未来的研究方向做出展望，以期进一步拓展流形学习的应用领域.
- Abstract:
- As a new unsupervised learning method, manifold learning is capturing increasing interests of researchers in the field of machine learning and cogniti ve sciences. To understand manifold learning better, the topology concept of man ifold learning was presented firstly, and then its development history was trace d. Based on different representations of manifold, several major algo rithms were introduced, whose advantages and defects were pointed out resp ectively. After that , two kinds of typical applications of Isomap and LLE were indicated. The res ults show th at compared with traditional linear method, manifold learning can discover the in trinsic dimensions of nonlinear highdimensional data effectively, helping re searchers to reduce dimensionality and analyze data better. Finally the prospect of manifold learning was discussed, so as to extend the application area of man ifold learning.
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备注/Memo
收稿日期：2006-03-01.
基金项目：国家自然科学基金资助项目(60332010，60533030).
作者简介：
徐???? 蓉，女，1982年生，哈尔滨工业大学在读硕士研究生，主要研究方向为模式识别、机器学习、手语识别.
姜???? 峰，在职博士研究生，讲师.主要研究方向为模式识别、机器学习、自然人机交互技术、多媒体技术、数字版权保护等.
姚鸿勋，教授，博导.主要研究方向为自然人机交互技术、多媒体技术、图像处理及模式识别、信息隐藏与检测、数字版权保护、生物特征识别技术等.已发表学术论文60余篇，其中被SCI、EI、 ISTP检索收录30余篇，另获发明专利1项.
更新日期/Last Update:
2009-04-07