Companies providing cloud-scale services have an increasing need to store and analyze massive data sets such as search logs and click streams. For cost and performance reasons, pr...
In this paper, we propose a new nonparametric Bayesian framework to cluster white matter fiber tracts into bundles using a hierarchical Dirichlet processes mixture (HDPM) model. Th...
Carl-Fredrik Westin, W. Eric L. Grimson, Xiaogang ...
Process Mining refers to the extraction of process models from event logs. Real-life processes tend to be less structured and more flexible. Traditional process mining algorithms...
R. P. Jagadeesh Chandra Bose, Wil M. P. van der Aa...
—Two strategies of distribution of computations can be used to implement parallel solvers for dense linear algebra problems for Heterogeneous Computational Clusters of Multicore ...
—In Dirichlet process (DP) mixture models, the number of components is implicitly determined by the sampling parameters of Dirichlet process. However, this kind of models usually...