We investigate full-scale shortest-derivation parsing (SDP), wherein the parser selects an analysis built from the fewest number of training fragments. Shortest derivation parsing...
— Incremental rule base learning techniques can be used to learn models and classifiers from interval or fuzzyvalued data. These algorithms are efficient when the observation e...
We develop, analyze, and test a training algorithm for support vector machine classifiers without offset. Key features of this algorithm are a new, statistically motivated stoppi...
The paper presents an efficient solution to decision problems where direct partial information on the distribution of the states of nature is available, either by observations of ...
A texture atlas is an efficient way to represent information (like colors, normals, displacement maps ...) on triangulated surfaces. The LSCM method (Least Squares Conformal Maps...