We examine how a network of many knowledge layers can be constructed in an on-line manner, such that the learned units represent building blocks of knowledge that serve to compres...
Abstract. Capturing regularities in high-dimensional data is an important problem in machine learning and signal processing. Here we present a statistical model that learns a nonli...
Abstract—Handling mobility at the transport layer is a promising approach to achieve seamless handover in the context of heterogeneous wireless access networks. In particular, fe...
The generalized multiprotocol label switching (GMPLS) networks attain a hierarchical structure, and each layer maintains an independent protection mechanism, resulting in redundant...
We consider the problem of learning in multilayer feed-forward networks of linear threshold units. We show that the Vapnik-Chervonenkis dimension of the class of functions that ca...