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...
In this paper, we consider the communications involved in the execution of a complex application, deployed on a heterogeneous platform. Such applications extensively use macro-com...
This paper develops a weakly supervised algorithm that learns to segment rigid multi-colored objects from a set of training images and key points. The approach uses congealing to ...
Douglas Moore, John Stevens, Scott Lundberg, Bruce...
We introduce a generative model of dense flow fields within a layered representation of 3-dimensional scenes. Using probabilistic inference and learning techniques (namely, varia...
Clustering and prediction of sets of curves is an important problem in many areas of science and engineering. It is often the case that curves tend to be misaligned from each othe...