The Compressive Sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by reducing the sampling rate required to acquire and stably recover sparse s...
Laurent Jacques, Jason N. Laska, Petros Boufounos,...
We present a new general class of methods for the computation of high-dimensional integrals. The quadrature schemes result by truncation and discretization of the anchored-ANOVA d...
Capacitance extraction is an important problem that has been extensively studied. This paper presents a significant improvement for the fast multipole accelerated boundary element...
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Algorithms such as Least Median of Squares (LMedS) and Random Sample Consensus (RANSAC) have been very successful for low-dimensional robust regression problems. However, the comb...