Deformable template models, in which a shape model and its corresponding appearance model are deformed to optimally fit an object in the image, have proven successful in many medic...
In this paper we investigate the regularization property of Kernel Principal Component Analysis (KPCA), by studying its application as a preprocessing step to supervised learning ...
We present an algorithm, HI-MAT (Hierarchy Induction via Models And Trajectories), that discovers MAXQ task hierarchies by applying dynamic Bayesian network models to a successful...
The problem of learning a transduction, that is a string-to-string mapping, is a common problem arising in natural language processing and computational biology. Previous methods ...
We consider support vector machines for binary classification. As opposed to most approaches we use the number of support vectors (the "L0 norm") as a regularizing term ...