The problem of managing the evolution of complex and large software systems is well known. Evolution implies reuse and modification of existing software artifacts, and this means t...
Maximum a Posteriori assignment (MAP) is the problem of finding the most probable instantiation of a set of variables given the partial evidence on the other variables in a Bayesi...
As real-world Bayesian networks continue to grow larger and more complex, it is important to investigate the possibilities for improving the performance of existing algorithms of ...
Generalized belief propagation (GBP) has proven to be a promising technique for approximate inference tasks in AI and machine learning. However, the choice of a good set of cluste...
Large web or e-commerce sites are frequently hosted on clusters. Successful open-source tools exist for clustering the front tiers of such sites (web servers and application serve...