The MPI programming model hides network type and topology from developers, but also allows them to seamlessly distribute a computational job across multiple cores in both an intra ...
Probabilistic models have been adopted for many computer vision applications, however inference in highdimensional spaces remains problematic. As the statespace of a model grows, ...
For decades, Hidden Markov Models (HMMs) have been the state-of-the-art technique for acoustic modeling despite their unrealistic independence assumptions and the very limited rep...
ARIMA is a popular method to analyze stationary univariate time series data. There are usually three main stages to build an ARIMA model, including model identification, model est...
Abstract— Graphical variant modeling refers to a novel approach to object-oriented modeling whereby a class overrides behavior inherited from a parent class by specifying variati...