In this paper, an adaptive sampling method is proposed for the statistical SRAM cell analysis. The method is composed of two components. One part is the adaptive sampler that manip...
Time series data is common in many settings including scientific and financial applications. In these applications, the amount of data is often very large. We seek to support pred...
Recently, several manifold learning algorithms have been proposed, such as ISOMAP (Tenenbaum et al., 2000), Locally Linear Embedding (Roweis & Saul, 2000), Laplacian Eigenmap ...
Background: Regulation of gene expression is relevant to many areas of biology and medicine, in the study of treatments, diseases, and developmental stages. Microarrays can be use...
The graphical depiction of uncertainty information is emerging as a problem of great importance. Scientific data sets are not considered complete without indications of error, acc...
Kristin Potter, Joe Kniss, Richard F. Riesenfeld, ...