We investigate the empirical applicability of several bounds (a number of which are new) on the true error rate of learned classifiers which hold whenever the examples are chosen ...
This chapter discusses decision making under uncertainty. More specifically, it offers an overview of efficient Bayesian and distribution-free algorithms for making near-optimal se...
Abstract. In this paper we discuss the automatic construction of webbased courseware applications from XML descriptions of appropriate UML models. The created applications conform ...
Andreas Papasalouros, Symeon Retalis, Nikolaos Pap...
This paper presents an adaptation of Luc Steels’s model of Category Formation and Language Sharing. The simple competitive learning algorithm is proposed as a more general means ...
Bounds are given for the empirical and expected Rademacher complexity of classes of linear transformations from a Hilbert space H to a ...nite dimensional space. The results imply ...