Dimensionality reduction is an important issue when facing high-dimensional data. For supervised dimensionality reduction, Linear Discriminant Analysis (LDA) is one of the most po...
Feiping Nie, Shiming Xiang, Yangqiu Song, Changshu...
Clustering large data sets with high dimensionality is a challenging data-mining task. This paper presents a framework to perform such a task efficiently. It is based on the notio...
Ying Lai, Ratko Orlandic, Wai Gen Yee, Sachin Kulk...
Three-dimensional integration technologies have been proposed in order to mitigate design challenges posed by deep-submicron interconnect. By providing multiple layers of active d...
The reduction of dynamic systems has a rich history, with many important applications related to stability, control and verification. Reduction of nonlinear systems is typically p...
Paulo Tabuada, Aaron D. Ames, A. Agung Julius, Geo...
Abstract. There has been growing interest in developing nonlinear dimensionality reduction algorithms for vision applications. Although progress has been made in recent years, conv...