We present a multi-label multiple kernel learning (MKL) formulation in which the data are embedded into a low-dimensional space directed by the instancelabel correlations encoded ...
The MAP (maximum a posteriori hypothesis) problem in Bayesian networks is to find the most likely states of a set of variables given partial evidence on the complement of that set...
We present an algorithm that derives actions' effects and preconditions in partially observable, relational domains. Our algorithm has two unique features: an expressive rela...
For headphone-based spatial auditory display systems, binaural synthesis of sound localization cues typically use source reproduction level as the primary control for source range...
Over the last years, particle filters have been applied with great success to a variety of state estimation problems. We present a statistical approach to increasing the efficienc...