We argue that K–means and deterministic annealing algorithms for geometric clustering can be derived from the more general Information Bottleneck approach. If we cluster the ide...
Incremental conceptual clustering is an important area of machine learning. It is concerned with summarizing data in a form of concept hierarchies, which will eventually ease the ...
We present a state of the art read-only distributed shared memory (DSM) ray tracer capable of fully utilizing modern cluster hardware to render massive out-of-core polygonal model...
Abstract— This paper describes a novel algorithm for autonomous and incremental learning of motion pattern primitives by observation of human motion. Human motion patterns are ed...
Recently, the analysis of moving objects has become one of the most important technologies to be used in various applications such as GIS, navigation systems, and locationbased in...