We consider the problem of classification when multiple observations of a pattern are available, possibly under different transformations. We view this problem as a special case o...
For software and more illustrations: http://www.psi.utoronto.ca/anitha/fastTCA.htm Dimensionality reduction techniques such as principal component analysis and factor analysis are...
Many computer vision and pattern recognition algorithms are very sensitive to the choice of an appropriate distance metric. Some recent research sought to address a variant of the...
We present an information theoretic approach for learning a linear dimension reduction transform for object classification. The theoretic guidance of the approach is that the trans...
The linear discriminant analysis (LDA) technique is very popular in pattern recognition for dimensionality reduction. It is a supervised learning technique that finds a linear tran...