Traditional face superresolution methods treat face images as 1D vectors and apply PCA on the set of these 1D vectors to learn the face subspace. Zhang et al [7] proposed Two-dire...
A probabilistic power estimation technique for combinational circuits is presented. A novel set of simple waveforms is the kernel of this technique. The transition density of each...
Saeeid Tahmasbi Oskuii, Per Gunnar Kjeldsberg, Ein...
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
One way to address the continuing performance problem of high-level domain-specific languages, such as Octave or MATLAB, is to compile them to a relatively lower level language f...
With the increasing gap between processor speed and memory latency, the performance of data-dominated programs are becoming more reliant on fast data access, which can be improved...