A hybrid approach that utilizes both statistical techniques and empirical methods seeks to provide more information about the performance of an application. In this paper, we prese...
Abstract. Many applications of machine learning involve sparse highdimensional data, where the number of input features is (much) larger than the number of data samples, d n. Predi...
Finding effective methods for developing an ensemble of models has been an active research area of large-scale data mining in recent years. Models learned from data are often subj...
— An effectively designed and efficiently used memory hierarchy, composed of scratch-pads or cache, is seen today as the key to obtaining energy and performance gains in data-do...
Background: Sustained research on the problem of determining which genes are differentially expressed on the basis of microarray data has yielded a plethora of statistical algorit...