In this paper, we compare performance of several dimension reduction techniques, namely LSI, FastMap, and SDD in Iris recognition. We compare the quality of these methods from both...
Due to the tremendous increase of electronic information with respect to the size of data sets as well as their dimension, dimension reduction and visualization of high-dimensiona...
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...
This paper presents a unified view of a number of dimension reduction techniques under the common framework of tensors. Specifically, it is established that PCA, and the recentl...
In this paper, we compare performance of several dimension reduction techniques, namely SVD, NMF and SDD.The qualitative comparison is evaluated on a collection of bars. We compare...