Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
Theperformanceofvariousorganizationalstructuresisanessentialparameterinthereengineeringoforganizations, particularly in the current rapidly changing, competitive and information t...
Abstract. Learning-based approaches have become increasingly practical in medical imaging. For a supervised learning strategy, the quality of the trained algorithm (usually a class...
Juan Eugenio Iglesias, Cheng-Yi Liu, Paul M. Thomp...
This paper presents a novel method for learning object manipulation such as rotating an object or placing one object on another. In this method, motions are learned using referenc...
The kernel Perceptron is an appealing online learning algorithm that has a drawback: whenever it makes an error it must increase its support set, which slows training and testing ...