We consider the problem of multiple kernel learning (MKL), which can be formulated as a convex-concave problem. In the past, two efficient methods, i.e., Semi-Infinite Linear Prog...
Abstract— Opportunistic Networks (ONs) are a newly emerging type of Delay Tolerant Network (DTN) systems that opportunistically exploit unplanned contacts among nodes to share in...
PropBank has been widely used as training data for Semantic Role Labeling. However, because this training data is taken from the WSJ, the resulting machine learning models tend to...
The OMNeT++ discrete event simulation environment has been publicly available since 1997. It has been created with the simulation of communication networks, multiprocessors and ot...
In this paper we present DeSiNe, a modular flow-level network simulator. DeSiNe is aimed at performance analysis and benchmarking of Quality of Service routing algorithms and traf...
Tom Kleiberg, Bingjie Fu, Fernando A. Kuipers, Pie...