The hierarchical Dirichlet process hidden Markov model (HDP-HMM) is a flexible, nonparametric model which allows state spaces of unknown size to be learned from data. We demonstra...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
Input modeling that involves fitting standard univariate parametric probability distributions is typically performed using an input modeling package. These packages typically fit ...
In most distributed systems, naming of nodes for low-level communication leveragestopologicallocation(such as node addresses) and is independentof any application. In this paper, ...
John S. Heidemann, Fabio Silva, Chalermek Intanago...
For a grid middleware to perform resource allocation, prediction models are needed, which can determine how long an application will take for completion on a particular platform o...
These days an increasing number of applications, especially in science and engineering, are dealing with a massive amount of data; hence they are dataintensive. Bioinformatics, da...