— Network clustering enables us to view a complex network at the macro level, by grouping its nodes into units whose characteristics and interrelationships are easier to analyze ...
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
Current exact algorithms for score-based structure discovery in Bayesian networks on n nodes run in time and space within a polynomial factor of 2n . For practical use, the space ...
In this thesis we compare several machine learning techniques for evaluating external skeletal fixation proposals. We experimented in the context of dog bone fractures but the pot...
Ning Suo, Khaled Rasheed, Walter D. Potter, Dennis...
In this paper, we explore the use of hierarchically structured multiprocessor tasks (M-tasks) for programming multi-core cluster systems. These systems often have hierarchically s...