We present a framework for clustering distributed data in unsupervised and semi-supervised scenarios, taking into account privacy requirements and communication costs. Rather than...
A key problem in model checking open systems is environment modeling (i.e., representing the behavior of the execution context of the system under analysis). Software systems are ...
Oksana Tkachuk, Matthew B. Dwyer, Corina S. Pasare...
Recently, generative probabilistic modeling principles were extended to visualization of structured data types, such as sequences. The models are formulated as constrained mixture...
Formal languages for probabilistic modeling enable re-use, modularity, and descriptive clarity, and can foster generic inference techniques. We introduce Church, a universal langu...
Noah Goodman, Vikash K. Mansinghka, Daniel M. Roy,...
Statistical shape modeling using point distribution models (PDMs) has been studied extensively for segmentation and other image analysis tasks. Methods investigated in the literat...
Geremy Heitz, Torsten Rohlfing, Calvin R. Maurer J...