Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Mixture model clustering for mixed data with missing information
Computational Statistics & Data Analysis
Proceedings of the 10th annual conference on Genetic and evolutionary computation
The effects of heterogeneity on asynchronous panmictic genetic search
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Accelerating the MilkyWay@Home volunteer computing project with GPUs
PPAM'09 Proceedings of the 8th international conference on Parallel processing and applied mathematics: Part I
A self-adaptive computing framework for parallel maximum likelihood evaluation
The Journal of Supercomputing
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Data from the Sloan Digital Sky Survey has given evidence of structures within the Milky Way halo from other nearby galaxies. Both the halo and these structures are approximated by densities based on geometric objects. A model of the data is formed by a mixture of geometric densities. By using an EM-style algorithm, we optimize the parameters of our model in order to separate out these structures from the data and thus obtain an accurate dataset of the Milky Way.