In this paper, we address a fundamental problem concerning the best flooding strategy to minimize cost and latency for target discovery in wireless networks. Should we flood the ...
A fundamental assumption for any machine learning task is to have training and test data instances drawn from the same distribution while having a sufficiently large number of tra...
Ontologies are an emerging paradigm to support declarativity, interoperability, and intelligent services in many areas, such as Agent–based Computation, Distributed Information ...
In many optimization problems, one seeks to allocate a limited set of resources to a set of individuals with demands. Thus, such allocations can naturally be viewed as vectors, wi...
a useful abstract representation is fundamental to solving many difficult problems in software engineering. In order to better understand how representations are actually used in ...