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...
We propose an efficient method for complex optimization problems that often arise in computer vision. While our method is general and could be applied to various tasks, it was mai...
Subthreshold circuit designs have been demonstrated to be a successful alternative when ultra-low power consumption is paramount. However, the characteristics of MOS transistors i...
John Keane, Hanyong Eom, Tae-Hyoung Kim, Sachin S....
Boundeddegreenetworks like deBruijn graphsor wrapped butterfly networks are very important from VLSI implementation point of view as well as for applications where the computing n...
We present an optimization method and algorithm designed for three objectives: physical data independence, semantic optimization, and generalized tableau minimization. The method ...