We consider approximation algorithms for buy-at-bulk network design, with the additional constraint that demand pairs be protected against edge or node failures in the network. In...
Spyridon Antonakopoulos, Chandra Chekuri, F. Bruce...
Background: With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few appro...
Grace S. Shieh, Chung-Ming Chen, Ching-Yun Yu, Jui...
—Different physical impairments can occur in optical transmission systems. Impairments such as fiber nonlinear effects are dependent on network state and vary with traffic and to...
Wenhao Lin, Timothy Hahn, Richard S. Wolff, Brenda...
Many real life domains contain a mixture of discrete and continuous variables and can be modeled as hybrid Bayesian Networks (BNs). An important subclass of hybrid BNs are conditi...
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. denite clause programs containing probabilistic facts with a ...