We develop an intuitive geometric interpretation of the standard support vector machine (SVM) for classification of both linearly separable and inseparable data and provide a rigo...
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 ...
This paper presents a new approach to extracting and representing structural features of images. The approach is based on both a region-based analysis and a contour-based analysis...
Every simple planar polygon can undergo only a finite number of pocket flips before becoming convex. Since Erdos posed this as an open problem in 1935, several independent purport...
Erik D. Demaine, Blaise Gassend, Joseph O'Rourke, ...
We study online classification of isolated handwritten symbols using distance measures on spaces of curves. We compare three distance-based measures on a vector space representatio...