In many applications, modelling techniques are necessary which take into account the inherent variability of given data. In this paper, we present an approach to model class speciļ...
This paper investigates incremental multiagent learning in static or evolving structured networks. Learning examples are incrementally distributed among the agents, and the object...
Gauvain Bourgne, Amal El Fallah-Seghrouchni, Henry...
The human ability to learn diļ¬cult object categories from just a few views is often explained by an extensive use of knowledge from related classes. In this work we study the use...
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....