Due to the well-known dimensionality curse problem, search in a high-dimensional space is considered as a "hard" problem. In this paper, a novel symmetrical encoding-bas...
Yi Zhuang, Yueting Zhuang, Qing Li, Lei Chen 0002,...
We present a new visualization of the distance and cluster structure of high dimensional data. It is particularly well suited for analysis tasks of users unfamiliar with complex d...
Flow cytometry technique produces large, multidimensional datasets of properties of individual cells that are helpful for biomedical science and clinical research. This paper expl...
Lin Liu, Li Xiong, James J. Lu, Kim M. Gernert, Vi...
Mean shift is a popular approach for data clustering, however, the high computational complexity of the mean shift procedure limits its practical applications in high dimensional ...
In [1], three popular subspace face recognition methods, PCA, Bayes, and LDA were analyzed under the same framework and an unified subspace analysis was proposed. However, since t...