We extend the differential approach to inference in Bayesian networks (BNs) (Darwiche, 2000) to handle specific problems that arise in the context of dynamic Bayesian networks (D...
We consider the problem of structured classification, where the task is to predict a label y from an input x, and y has meaningful internal structure. Our framework includes super...
Peter L. Bartlett, Michael Collins, Benjamin Taska...
We describe the application of kernel methods to Natural Language Processing (NLP) problems. In many NLP tasks the objects being modeled are strings, trees, graphs or other discre...
Modern object-oriented programs are hierarchical systems with many thousands of interrelated subsystems. Visualization helps developers to better comprehend these large and comple...
Michael Balzer, Andreas Noack, Oliver Deussen, Cla...
Creating a simulation of a large enterprise system by manually coding all the details into a simulator tool is not just time consuming, but yields a system that is difficult to ma...
Gregory A. Harrison, David S. Maynard, Eytan Polla...