This paper introduces GNARL, an evolutionary program which induces recurrent neural networks that are structurally unconstrained. In contrast to constructive and destructive algor...
Gregory M. Saunders, Peter J. Angeline, Jordan B. ...
We show that there is a trade-off among mobility, capacity, and delay in ad hoc networks. More specifically, we consider two schemes for node mobility in ad hoc networks. We divid...
Renato M. de Moraes, Hamid R. Sadjadpour, J. J. Ga...
Encouraging the release of network data is central to promoting sound network research practices, though the publication of this data can leak sensitive information about the publ...
Scott E. Coull, Charles V. Wright, Fabian Monrose,...
Emerging high-end applications require a rich set of network provisioning services that go beyond the traditional source-destination, end-to-end path service. They also require hig...
Abstract. In this paper we investigate the feed-forward learning problem. The well-known ill-conditioning which is present in most feed-forward learning problems is shown to be the...