Isomap is one of widely-used low-dimensional embedding methods, where geodesic distances on a weighted graph are incorporated with the classical scaling (metric multidimensional s...
The last decade has witnessed a tremendous growths of interests in applications that deal with querying and mining of time series data. Numerous representation methods for dimensi...
Hui Ding, Goce Trajcevski, Peter Scheuermann, Xiao...
This paper presents a novel approach for the visualization and clustering of crowd video contents by using multilinear principal component analysis (MPCA). In contrast to feature-...
Singular Value Decomposition (and Principal Component Analysis) is one of the most widely used techniques for dimensionality reduction: successful and efficiently computable, it ...
The accuracy of methods for the assessment of mammographic risk analysis is heavily related to breast tissue characteristics. Previous work has demonstrated considerable success i...
Neil MacParthalain, Richard Jensen, Qiang Shen, Re...