Abstract. We propose motion manifold learning and motion primitive segmentation framework for human motion synthesis from motion-captured data. High dimensional motion capture date...
This paper presents a learning system that uses genetic programming as a tool for automatically inferring the set of classification rules to be used during a preclassification sta...
Claudio De Stefano, Antonio Della Cioppa, Angelo M...
A hybrid system is described which combines the strength of manual rulewriting and statistical learning, obtaining results superior to both methods if applied separately. The comb...
Jan Hajic, Pavel Krbec, Pavel Kveton, Karel Oliva,...
In this paper we provide a fast, data-driven solution to the failing query problem: given a query that returns an empty answer, how can one relax the query's constraints so t...
Abstract. We present The Cruncher, a simple representation framework and algorithm based on minimum description length for automatically forming an ontology of concepts from attrib...