Large distributed Grid systems pose new challenges in job scheduling due to complex workload characteristics and system characteristics. Due to the numerous parameters that must b...
Due to the strong increase of processing units available to the end user, expressing parallelism of an algorithm is a major challenge for many researchers. Parallel applications ar...
In the Bayesian mixture modeling framework it is possible to infer the necessary number of components to model the data and therefore it is unnecessary to explicitly restrict the n...
System reliability has become an increasingly important benchmark in measuring service continuity. As part of many service level agreements, system performance is gauged by how lo...
Recent work has exploited boundedness of data in the unsupervised learning of new types of generative model. For nonnegative data it was recently shown that the maximum-entropy ge...