Using concepts from rough set theory we investigate the existence of approximative descriptions of collections of objects that can be extracted from data sets, a problem of intere...
: Numerical function approximation over a Boolean domain is a classical problem with wide application to data modeling tasks and various forms of learning. A great many function ap...
The increasing prominence of data streams arising in a wide range of advanced applications such as fraud detection and trend learning has led to the study of online mining of freq...
We present a new data structure that facilitates approximate nearest neighbor searches on a dynamic set of points in a metric space that has a bounded doubling dimension. Our data...
We consider the problem of approximating a family of isocontours in a sensor field with a topologically-equivalent family of simple polygons. Our algorithm is simple and distribu...