In this paper we first overview the main concepts of Statistical Learning Theory, a framework in which learning from examples can be studied in a principled way. We then briefly di...
Parallel and distributed information processing systems play an increasingly important role in artificial intelligence and computer science. In this article an approach to learnin...
This paper reports a study that aims to construct a 2D barcode supported learning system, called HELLO (Handheld English Language Learning Organization), to improve students’ En...
In this paper, we consider the asymptotic form of the generalization error for the restricted Boltzmann machine in Bayesian estimation. It has been shown that obtaining the maximu...
Abstract. In this paper, we propose and study a new on-line algorithm for learning a SVM based on Radial Basis Function Kernel: Local Incremental Learning of SVM or LISVM. Our meth...