This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Today's high-end massively parallel processing (MPP) machines have thousands to tens of thousands of processors, with next-generation systems planned to have in excess of one...
Ron Oldfield, Lee Ward, Rolf Riesen, Arthur B. Mac...
Setting up generic and fully transparent distributed services for clusters implies complex and tedious kernel developments. More flexible approaches such as user-space libraries ar...
Adrien Lebre, Renaud Lottiaux, Erich Focht, Christ...
Distance functions are an important component in many learning applications. However, the correct function is context dependent, therefore it is advantageous to learn a distance f...
Accurate grouping of video shots could lead to semantic indexing of video segments for content analysis and retrieval. This paper introduces a novel cluster analysis which, depend...