Spatial classification is the task of learning models to predict class labels based on the features of entities as well as the spatial relationships to other entities and their fe...
Many large-scale networks such as ad hoc and sensor networks, peer-to-peer networks, or the Internet have the property that the number of independent nodes does not grow arbitrari...
This paper shows that the accuracy of learned text classifiers can be improved by augmenting a small number of labeled training documents with a large pool of unlabeled documents. ...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
We present several efficient dynamic data structures for point-enclosure queries, involving convex fat objects in R2 or R3. Our planar structures are actually fitted for a more ...
Alon Efrat, Matthew J. Katz, Frank Nielsen, Micha ...
Abstract. We are interested in efficient algorithms for generating random samples from geometric objects such as Riemannian manifolds. As a step in this direction, we consider the ...