Mining graph patterns in large networks is critical to a variety of applications such as malware detection and biological module discovery. However, frequent subgraphs are often i...
Many algorithms for processing probabilistic networks are dependent on the topological properties of the problem's structure. Such algorithmse.g., clustering, conditioning ar...
The traditional approach to building Bayesian networks is to build the graphical structure using a graphical editor and then add probabilities using a separate spreadsheet for eac...
Previous researchers note the problem for semantic optimisation of database queries caused by its production of a large number of semantically equivalent alternative queries, from...
Abstract— Motivated by applications to sensor, peer-topeer and ad hoc networks, we study distributed asynchronous algorithms, also known as gossip algorithms, for computation and...
Stephen P. Boyd, Arpita Ghosh, Balaji Prabhakar, D...