In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
Avrim Blum, John D. Lafferty, Mugizi Robert Rweban...
Recently, spectral clustering (a.k.a. normalized graph cut) techniques have become popular for their potential ability at finding irregularlyshaped clusters in data. The input to...
Given a set S of line segments in the plane, we introduce a new family of partitions of the convex hull of S called segment triangulations of S. The set of faces of such a triangul...
Spectral clustering refers to a class of techniques which rely on the eigenstructure of a similarity matrix to partition points into disjoint clusters, with points in the same clu...
Five-axis machining of sculptured surfaces is gaining wider acceptance in many industries. This paper examines the potential of a new tool positioning strategy where the desired s...