Tensor Graph-optimized Linear Discriminant Analysis

Jianjun Chen

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Tensor Graph-optimized Linear Discriminant Analysis

机译：张量图优化的线性判别分析

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摘要

Graph-based Fisher Analysis (GbFA) is proposed recently for dimensionality reduction, which has the powerful discriminant ability. However, GbFA is based on the matrix-to-vector way, which not only costs much but also loses spatial relations of pixels in images. Therefore, Tensor Graph-based Linear Discriminant Analysis (TGbLDA) is proposed in the paper. TGbLDA regards samples as data in tensor space and gets projection matrixes through the iteration way. Besides, TGbLDA inherits merits of GbFA. Experiments on Yale and YaleB face datasets demonstrate the effectiveness of our proposed algorithm.

机译：最近提出了基于图的Fisher分析（GbFA）用于降维，它具有强大的判别能力。但是，GbFA基于矩阵到矢量的方式，不仅成本高昂，而且还会丢失图像中像素的空间关系。因此，本文提出了基于张量图的线性判别分析（TGbLDA）。 TGbLDA将样本视为张量空间中的数据，并通过迭代方式获取投影矩阵。此外，TBgLDA继承了GbFA的优点。在Yale和YaleB人脸数据集上进行的实验证明了我们提出的算法的有效性。

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《Journal of digital information management》 |2014年第1期|31-35|共5页
作者
Jianjun Chen;
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作者单位

Department of Information and Electron of Yuanpei of College Shaoxing University Shaoxing Shaoxing 312000 China;

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原文格式 PDF
正文语种 eng
中图分类
关键词
Dimensionality Reduction; Graph-based Fisher Discriminant Analysis; Tensor Data; Face Recognition;

机译：降维;基于图的Fisher判别分析;张量数据人脸识别;

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1. Semi-supervised Tensor Graph-optimized Linear Discriminant Analysis for Two-dimensional Face Recognition [J] . Shuhua Xu Journal of software . 2013,第8期

机译：二维人脸识别的半监督张量图优化线性判别分析
2. Semi-supervised Tensor Graph-optimized Linear Discriminant Analysis for Two-dimensional Face Recognition [J] . Shuhua Xu Journal of software . 2013,第8期

机译：二维人脸识别的半监督张量图优化线性判别分析
3. Orthogonal multilinear discriminant analysis and its subblock tensor analysis version [J] . Ben Xianye, Jiang Mingyan, Yan Rui, Optik: Zeitschrift fur Licht- und Elektronenoptik: = Journal for Light-and Electronoptic . 2015,第3期

机译：正交多线性判别分析及其子块张量分析版本
4. Graph-Optimized Line Discriminant Analysis for Face Recognition [C] . Wu Wentie, Lu Yingchun, Chen Xuelin International Symposium on Computational Intelligence and Design;ISCID 2012 . 2012

机译：图优化的线判别分析用于人脸识别
5. A COMPARISON OF SIX MODELS FOR PREDICTING CORPORATE BANKRUPTCY: MULTIPLE LINEAR REGRESSION ANALYSIS, MULTIPLE LINEAR DISCRIMINANT ANALYSIS, STEPWISE REGRESSION ANALYSIS, STEPWISE DISCRIMINANT ANALYSIS, MULTIPLE LINEAR REGRESSION ANALYSIS WITH RIDGE REGRESSION, AND MULTIPLE LINEAR DISCRIMINANT ANALYSIS WITH BIASED MINIMUM CHI-SQUARE RULE [D] . MAPP, JOHNNIE ALBERT. 1981

机译：六种预测公司破产的模型的比较：多个线性回归分析，多个线性判别分析，逐步回归分析，逐步判别分析，多个带岭点回归的线性回归分析，以及多个线性离散
6. Incremental Discriminant Analysis in Tensor Space [O] . Liu Chang, Zhao Weidong, Yan Tao, 2015

机译：张量空间中的增量判别分析
7. Uncorrelated multilinear discriminant analysis with regularization and aggregation for tensor object recognition [O] . Haiping Lu, K. N. Plataniotis, A. N. Venetsanopoulos 2009

机译：具有正则化和聚合的不相关多线性判别分析用于张量目标识别

Tensor Graph-optimized Linear Discriminant Analysis

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