A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a ...
Visual media data such as an image is the raw data representation for many important applications. Reducing the dimensionality of raw visual media data is desirable since high dime...
Many emerging data mining applications require a similarity join between points in a high-dimensional domain. We present a new algorithm that utilizes a new index structure, calle...
Data mining tasks results are usually improved by reducing the dimensionality of data. This improvement however is achieved harder in the case that data lay on a non linear manifol...
Multi-dimensional systems containing nested loops are widely used to model scientific applications such as image processing, geophysical signal processing and fluid dynamics. Ho...
Ted Zhihong Yu, Edwin Hsing-Mean Sha, Nelson L. Pa...