Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...
Collecting large consistent data sets for real world software projects is problematic. Therefore, we explore how little data are required before the predictor performance plateaus...
Abstract. In this paper, we describe an unsupervised learning framework to segment a scene into semantic regions and to build semantic scene models from longterm observations of mo...
Experience from the management of distributed computer-based learning resources in schools has been proven to be inefficient and costly. Though commercial software packages are av...
Due to its fixed assignment nature, the well-known time division multiple access (TDMA) protocol suffers from poor performance when the offered traffic is bursty. In this paper, an...
Georgios I. Papadimitriou, Mohammad S. Obaidat, An...