We present two novel methods to automatically learn spatio-temporal dependencies of moving agents in complex dynamic scenes. They allow to discover temporal rules, such as the rig...
Daniel Kuettel, Michael Breitenstein, Luc Van Gool...
The present paper analyzes a learning experience run at University of Macerata, during a post degree course for in service teachers and mature students. The course was delivered e...
—A fast online algorithm OnlineSVMR for training Ramp-Loss Support Vector Machines (SVMR s) is proposed. It finds the optimal SVMR for t+1 training examples using SVMR built on t...
In the first part we describe the dissemination of wikis in the German-speaking school community with a special focus on Switzerland, the most active German-speaking country using...
We introduce a new learning algorithm for topographic map formation of Edgeworth-expanded Gaussian activation kernels. In order to avoid the rapid increase in kernel parameters, a...