A common assumption in supervised learning is that the training and test input points follow the same probability distribution. However, this assumption is not fulfilled, e.g., in...
Presenting information to an e-learning environment is a challenge, mostly, because ofthe hypertextlhypermedia nature and the richness ofthe context and information provides. This...
We describe a learning based method for recovering 3D human body pose from single images and monocular image sequences. Our approach requires neither an explicit body model nor pr...
This paper describes a novel application of Statistical Learning Theory (SLT) to control model complexity in flow estimation. SLT provides analytical generalization bounds suitabl...
Zoran Duric, Fayin Li, Harry Wechsler, Vladimir Ch...
We prove the statistical consistency of kernel Partial Least Squares Regression applied to a bounded regression learning problem on a reproducing kernel Hilbert space. Partial Lea...