This paper introduces kernels on attributed pointsets, which are sets of vectors embedded in an euclidean space. The embedding gives the notion of neighborhood, which is used to d...
—Recent advances in DNA sequencing techniques have led to an unprecedented accumulation and availability of molecular sequence data that needs to be analyzed. This data explosion...
Point clouds are sets of points in two or three dimensions. Most kernel methods for learning on sets of points have not yet dealt with the specific geometrical invariances and pra...
Abstract. The presence of noise renders the classical factorization method almost impractical for real-world multi-body motion tracking problems. The main problem stems from the ef...
Background: Prediction of protein localization in subnuclear organelles is more challenging than general protein subcelluar localization. There are only three computational models...