Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...
High dimensionality remains a significant challenge for document clustering. Recent approaches used frequent itemsets and closed frequent itemsets to reduce dimensionality, and to...
Recently the problem of dimensionality reduction has received a lot of interests in many fields of information processing. We consider the case where data is sampled from a low d...
Multimedia similarity search has been playing a critical role in many novel applications. Typically, multimedia objects are described by high-dimensional feature vectors (or point...
Zi Huang, Heng Tao Shen, Jiajun Liu, Xiaofang Zhou
Research into optical markerless human motion capture has attracted significant attention. However, the complexity of the human anatomy, ambiguities introduced by lacking full-pe...