In this paper we propose the "Classification-Based Learning of Subsumption Relations for the Alignment of Ontologies" (CSR) method. Given a pair of concepts from two onto...
Vassilis Spiliopoulos, Alexandros G. Valarakos, Ge...
Abstract. This paper studies the properties and performance of models for estimating local probability distributions which are used as components of larger probabilistic systems ...
Kristina Toutanova, Mark Mitchell, Christopher D. ...
Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...
This paper proposes a logic for causal based on event trees. Event trees provide a natural and familiar framework for probability and decision theory, but they lack the modularity...
This paper proposes a system to relate objects in an image using occlusion cues and arrange them according to depth. The system does not rely on any a priori knowledge of the scen...