High dimensional data sets are encountered in many modern database applications. The usual approach is to construct a summary of the data set through a lossy compression technique...
A linear, discriminative, supervised technique for reducing feature vectors extracted from image data to a lower-dimensional representation is proposed. It is derived from classica...
Image databases are nowadays widely exploited in a number of different contexts, ranging from history of art, through medicine, to education. Existing querying paradigms are based ...
A fast and simple algorithm for approximately calculating the principal components (PCs) of a data set and so reducing its dimensionality is described. This Simple Principal Compo...
Similarity search in large time series databases has attracted much research interest recently. It is a difficult problem because of the typically high dimensionality of the data....
Eamonn J. Keogh, Kaushik Chakrabarti, Sharad Mehro...