首页> 外文期刊>Mathematical Problems in Engineering >Semisupervised Tangent Space Discriminant Analysis
【24h】

Semisupervised Tangent Space Discriminant Analysis

机译:半监督切线空间判别分析

获取原文
获取原文并翻译 | 示例
       

摘要

A novel semisupervised dimensionality reduction method named Semisupervised Tangent Space Discriminant Analysis (STSD) is presented, where we assume that data can be well characterized by a linear function on the underlying manifold. For this purpose, a new regularizer using tangent spaces is developed, which not only can capture the local manifold structure from both labeled and unlabeled data, but also has the complementarity with the Laplacian regularizer. Furthermore, STSD has an analytic form of the global optimal solution which can be computed by solving a generalized eigenvalue problem. To perform nonlinear dimensionality reduction and process structured data, a kernel extension of our method is also presented. Experimental results on multiple real-world data sets demonstrate the effectiveness of the proposed method.
机译:提出了一种新的半监督降维方法,称为半监督正切空间判别分析(STSD),我们假设数据可以通过底层流形上的线性函数很好地表征。为此,开发了一种使用切线空间的新正则化器,它不仅可以从标记和未标记的数据中捕获局部流形结构,而且与拉普拉斯正则化器具有互补性。此外,STSD具有可以通过解决广义特征值问题来计算的全局最优解的解析形式。为了进行非线性降维和处理结构化数据,还提出了我们方法的内核扩展。在多个实际数据集上的实验结果证明了该方法的有效性。

著录项

  • 来源
    《Mathematical Problems in Engineering》 |2015年第17期|706180.1-706180.10|共10页
  • 作者

    Zhou Yang; Sun Shiliang;

  • 作者单位

    E China Normal Univ, Dept Comp Sci & Technol, Shanghai Key Lab Multidimens Informat Proc, Shanghai 200241, Peoples R China.;

    E China Normal Univ, Dept Comp Sci & Technol, Shanghai Key Lab Multidimens Informat Proc, Shanghai 200241, Peoples R China.;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号