In many structured prediction problems, the highest-scoring labeling is hard to compute exactly, leading to the use of approximate inference methods. However, when inference is us...
Nearly every structured prediction problem in computer vision requires approximate inference due to large and complex dependencies among output labels. While graphical models prov...
We consider the problem of performing learning and inference in a large scale knowledge base containing imperfect knowledge with incomplete coverage. We show that a soft inference...
Abstract. In this survey paper we consider the class of protocols for informationhiding which use randomization to obfuscate the link between the observables and the information to...
In this survey paper we describethe combination of: discretized integral formulations, sparsication techniques, and krylov-subspace based model-order reduction that has led to rob...