In this paper, we present a novel on-line probabilistic generative model that simultaneously deals with both the clustering and the tracking of an unknown number of moving objects...
Suppose a set of images contains frequent occurrences of objects from an unknown category. This paper is aimed at simultaneously solving the following related problems: (1) unsupe...
Abstract. We consider a problem that is related to the “Universal Encoding Problem” from information theory. The basic goal is to find rules that map “partial information”...
This paper describes algorithms and software developed to characterise and detect generic intelligent language-like features iu an input signal, using Natural Language Learning te...
We study exploration problems where a robot has to construct a complete map of an unknown environment using a path that is as short as possible. In the rst problem setting we cons...