Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Getting agents in the Internet, and in networks in general, to invest in and deploy security features and protocols is a challenge, in particular because of economic reasons arisi...
—Aspnes et al [2] introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to i...
V. S. Anil Kumar, Rajmohan Rajaraman, Zhifeng Sun,...
Maximal clique enumeration (MCE) is a fundamental problem in graph theory and has important applications in many areas such as social network analysis and bioinformatics. The prob...
James Cheng, Yiping Ke, Ada Wai-Chee Fu, Jeffrey X...
Background: Reconstructing regulatory networks from gene expression profiles is a challenging problem of functional genomics. In microarray studies the number of samples is often ...
Barbara Di Camillo, Fatima Sanchez-Cabo, Gianna To...