Distributed learning is a problem of fundamental interest in machine learning and cognitive science. In this paper, we present asynchronous distributed learning algorithms for two...
Abstract We introduce some differences in the style defeasible information is represented and inferences are made in nonmonotonic reasoning. These, at first sight harmless, chang...
Marcelino C. Pequeno, Rodrigo de M. S. Veras, Wlad...
This paper proposes a novel approach for vehicle orientation detection using “vehicle color” and edge information based on clustering framework. To extract the “vehicle colo...
While current on-demand routing protocols are optimized to take into account unique features of mobile ad hoc networks (MANETs) such as frequent topology changes and limited batter...
Jay Boice, J. J. Garcia-Luna-Aceves, Katia Obraczk...
Learning application-specific distance metrics from labeled data is critical for both statistical classification and information retrieval. Most of the earlier work in this area h...