The field of stochastic optimization studies decision making under uncertainty, when only probabilistic information about the future is available. Finding approximate solutions to...
Image auto-annotation is an important open problem in
computer vision. For this task we propose TagProp, a discriminatively
trained nearest neighbor model. Tags of test
images a...
Matthieu Guillaumin, Thomas Mensink, Jakob Verbeek...
—One common approach to active learning is to iteratively train a single classifier by choosing data points based on its uncertainty, but it is nontrivial to design uncertainty ...
Abstract—The World Wide Web offers easy sharing of information, but provides only few options for the protection of sensitive information and other sensitive resources. Tradition...
Sergej Zerr, Daniel Olmedilla, Juri Luca De Coi, W...
Many research projects oriented on control mechanisms of virtual agents in videogames have emerged in recent years. However, this boost has not been accompanied with the emergence ...