With the amount of data in current data warehouse databases growing steadily, random sampling is continuously gaining in importance. In particular, interactive analyses of large d...
The inability to answer proximity queries efficiently for spaces of dimension d > 2 has led to the study of approximation to proximity problems. Several techniques have been pro...
Sunil Arya, Guilherme Dias da Fonseca, David M. Mo...
We address instance-based learning from a perceptual organization standpoint and present methods for dimensionality estimation, manifold learning and function approximation. Under...
—An approximate distance query data structure is a compact representation of a graph, and can be queried to approximate shortest paths between any pair of vertices. Any such data...
Rachit Agarwal, Philip Brighten Godfrey, Sariel Ha...
In many applications one is concerned with the approximation of functions from a finite set of scattered data sites with associated function values. We describe a scheme for cons...