Sparse coding of sensory data has recently attracted notable attention in research of learning useful features from the unlabeled data. Empirical studies show that mapping the data...
This paper introduces a geometrically inspired large-margin classifier that can be a better alternative to the Support Vector Machines (SVMs) for the classification problems with ...
Rendering highly complex models can be time and space prohibitive, and decimation is an important tool in providing simplifications. A decimated model may replace the original ent...
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Ro...
This paper presents a practical technique to automatically compute approximations of polygonal representations of 3D objects. It is based on a previously developed model simplific...