The prediction of protein secondary structure is a classical problem in bioinformatics, and in the past few years several machine learning techniques have been proposed to t. From...
This paper presents a new approach for representing multidimensional data by a compact number of bases. We consider the multidimensional data as tensors instead of matrices or vec...
Compressed sensing (CS) is a new technique for simultaneous data sampling and compression. In this paper, we propose and study block compressed sensing for natural images, where i...
In this paper we propose a new method that addresses the problem of tracking the bitmap (silhouette) of an object in a video under very general conditions. We assume a general tar...
In this paper we propose a novel parameterized macromodeling technique for analog circuits. Unlike traditional macromodels that are only extracted for a small variation space, our...