We consider the problem of learning Gaussian multiresolution (MR) models in which data are only available at the finest scale and the coarser, hidden variables serve both to captu...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
In order to retrieve, select and apply design patterns in a tool-supported way, we suggest to construct and document a problemcontext pattern that reflects the essence of the prob...
We present an overview of a tutorial on model management--an approach to solving data integration problems, such as data warehousing, e-commerce, object-to-relational mapping, sch...
Gaussian Markov random fields (GMRFs) are useful in a broad range of applications. In this paper we tackle the problem of learning a sparse GMRF in a high-dimensional space. Our a...
This paper introduced the application of a more efficient mathematical representation of the kinematics of avatars, or digital human beings, in telecollaborative virtual reality e...