Abstract-- In recent years, uncertain data management applications have grown in importance because of the large number of hardware applications which measure data approximately. F...
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
We present a description of three different algorithms that use background knowledge to improve text classifiers. One uses the background knowledge as an index into the set of tra...
Over the last decade, a number of methods for geometric matching based on a branch-and-bound approach have been proposed. Such algorithms work by recursively subdividing transforma...
We present a theory for constructing linear subspace approximations to face-recognition algorithms and empirically demonstrate that a surprisingly diverse set of face-recognition a...