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IEEEMM
2007
146views more  IEEEMM 2007»
15 years 6 months ago
Learning Microarray Gene Expression Data by Hybrid Discriminant Analysis
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
Yijuan Lu, Qi Tian, Maribel Sanchez, Jennifer L. N...
IJCAI
2007
15 years 7 months ago
Locality Sensitive Discriminant Analysis
Linear Discriminant Analysis (LDA) is a popular data-analytic tool for studying the class relationship between data points. A major disadvantage of LDA is that it fails to discove...
Deng Cai, Xiaofei He, Kun Zhou, Jiawei Han, Hujun ...
CVPR
2011
IEEE
15 years 2 months ago
Graph Embedding Discriminant Analysis on Grassmannian Manifolds for Improved Image Set Matching
A convenient way of dealing with image sets is to represent them as points on Grassmannian manifolds. While several recent studies explored the applicability of discriminant analy...
Mehrtash Harandi, Sareh, Shirazi (National ICT Aus...
ICPR
2008
IEEE
16 years 21 days ago
Semi-supervised marginal discriminant analysis based on QR decomposition
In this paper, a novel subspace learning method, semi-supervised marginal discriminant analysis (SMDA), is proposed for classification. SMDA aims at maintaining the intrinsic neig...
Rui Xiao, Pengfei Shi
CVPR
2007
IEEE
16 years 8 months ago
Tensor Canonical Correlation Analysis for Action Classification
We introduce a new framework, namely Tensor Canonical Correlation Analysis (TCCA) which is an extension of classical Canonical Correlation Analysis (CCA) to multidimensional data ...
Tae-Kyun Kim, Shu-Fai Wong, Roberto Cipolla