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一种新的基于MMC和LSE的监督流形学习算法

袁暋 程雷 朱然刚 雷迎科

袁暋, 程雷, 朱然刚, 雷迎科. 一种新的基于MMC和LSE的监督流形学习算法. 自动化学报, 2013, 39(12): 2077-2089. doi: 10.3724/SP.J.1004.2013.02077
引用本文: 袁暋, 程雷, 朱然刚, 雷迎科. 一种新的基于MMC和LSE的监督流形学习算法. 自动化学报, 2013, 39(12): 2077-2089. doi: 10.3724/SP.J.1004.2013.02077
YUAN Min, CHENG Lei, ZHU Ran-Gang, LEI Ying-Ke. A New Supervised Manifold Learning Algorithm Based on MMC and LSE. ACTA AUTOMATICA SINICA, 2013, 39(12): 2077-2089. doi: 10.3724/SP.J.1004.2013.02077
Citation: YUAN Min, CHENG Lei, ZHU Ran-Gang, LEI Ying-Ke. A New Supervised Manifold Learning Algorithm Based on MMC and LSE. ACTA AUTOMATICA SINICA, 2013, 39(12): 2077-2089. doi: 10.3724/SP.J.1004.2013.02077

一种新的基于MMC和LSE的监督流形学习算法

doi: 10.3724/SP.J.1004.2013.02077
基金项目: 

国家自然科学基金(61272333,61273302,61005010),安徽省自然科学基金(1208085MF94,1208085MF98,1308085MF84)资助

详细信息
    作者简介:

    袁暋 合肥学院计算机科学与技术系副教授. 主要研究方向为计算机图形图像处理. 本文通信作者.E-mail:hfyuanmin@163.com

A New Supervised Manifold Learning Algorithm Based on MMC and LSE

Funds: 

Supported by National Natural Science Foundation of China (61272333, 61273302, 61005010), Natural Science Foundation of Anhui Province (1208085MF94, 1208085MF98, 1308085MF84)

  • 摘要: 针对局部样条嵌入算法 (Local spline embedding,LSE) 存在样本外点学习和无监督模式学习问题,本文提出了一种新颖的正交局部样条判别投影算法 (O-LSDP).该算法通过引入明确的线性映射关系,构建平移缩放模型,以及正交化特征子空间,从而使该算法能够应用于模式分类问题并显著改善了算法的分类识别能力.在标准人 脸数据库和植物叶片数据库上的实验结果验证了该算法的有效性与可行性.
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出版历程
  • 收稿日期:  2012-01-09
  • 修回日期:  2013-03-27
  • 刊出日期:  2013-12-20

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