large-scale structured prediction with approximate inference

by Jiaolong for Shogun Machine Learning Toolbox

The factor graph model in Shogun provides a good example on how to use structured output SVM to learn parameters of graphical model. However the compatibility with approximate inference has not yet been explored. In this project, three approximate inference algorithms will be implemented and evaluated on multilabel classification. Furthermore, to demonstrate the scalability for large-scale applications, two computer vision demos, image inpainting and figure-ground segmentation will be created.