We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Representing articulated objects as a graphical model has gained much popularity in recent years, often the root node of the graph describes the global position and orientation of...
An iterative algorithm for the reconstruction of natural images given only their contrast map is presented. The solution is neuro-physiologically inspired, where the retinal cells...
The Support Vector Machine (SVM) of Vapnik [9] has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions...
When modeling real-world decision-theoretic planning problems in the Markov decision process (MDP) framework, it is often impossible to obtain a completely accurate estimate of tr...
Karina Valdivia Delgado, Scott Sanner, Leliane Nun...