Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...
Due to their capability for expressing semantics and relationships among data objects, semi-structured documents have become a common way of representing domain knowledge. Compari...
Henry Tan, Tharam S. Dillon, Fedja Hadzic, Elizabe...
This paper aims at discovering community structure in rich media social networks, through analysis of time-varying, multi-relational data. Community structure represents the laten...
Yu-Ru Lin, Jimeng Sun, Paul Castro, Ravi B. Konuru...
In many applications of graphical models arising in computer vision, the hidden variables of interest are most naturally specified by continuous, non-Gaussian distributions. There...
Erik B. Sudderth, Alexander T. Ihler, William T. F...
Network data models are widely used to describe the connectivity between spatial features in GIS architectures. Recent applications demand that such models are editable in multius...
Petko Bakalov, Erik G. Hoel, Wee-Liang Heng, Vassi...