In this paper we analyze the computational power of random geometric networks in the presence of random (edge or node) faults considering several important network parameters. We ...
Bayesian KnowledgeBases (BKB)are a rule-based probabilistic modelthat extend BayesNetworks(BN), by allowing context-sensitive independenceand cycles in the directed graph. BKBshav...
We present a new bicriteria approximation algorithm for the degree-bounded minimum-cost spanning tree problem: Given an undirected graph with nonnegative edge weights and degree b...
The benefit of incorporating background knowledge in the learning process has been successfully demonstrated in numerous applications of ILP methods. Nevertheless the effect of inc...
Many computation-intensive or recursive applications commonly found in digital signal processing and image processing applications can be represented by data-flow graphs (DFGs). ...