Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Temporal patterns composed of symbolic intervals are commonly formulated with Allen's interval relations originating in temporal reasoning. This representation has severe dis...
In gene expression microarray data analysis, selecting a small number of discriminative genes from thousands of genes is an important problem for accurate classification of diseas...
Simultaneous multithreading (SMT) seeks to improve the computation throughput of a processor core by sharing primary resources such as functional units, issue bandwidth, and cache...
Tipp Moseley, Dirk Grunwald, Joshua L. Kihm, Danie...
Nervixxx introduces neural computing to overcome the limit of conventional performance systems1 that uses tangible computing and physical computing. Specifically, we utilized the ...