This paper proposes a novel hierarchical learning strategy to deal with the data sparseness problem in relation extraction by modeling the commonality among related classes. For e...
The Data Diffusion Machine is a scalable virtual shared memory architecture. A hierarchical network is used to ensure that all data can be located in a time bounded by O(logp), wh...
Henk L. Muller, Paul W. A. Stallard, David H. D. W...
— In the field of mobile robotics, trajectory details are seldom taken into account to qualify robot performance. Most metrics rely mainly on global results such as the total ti...
Distributed storage systems employ replicas or erasure code to ensure high reliability and availability of data. Such replicas create great amount of network traffic that negative...
The non-existence of an end-to-end path poses a challenge in adapting the traditional routing algorithms to delay tolerant networks (DTNs). Previous works include centralized rout...