We are motivated by a recently developed nonlinear inverse scale space method for image denoising [5, 6], whereby noise can be removed with minimal degradation. The additive noise ...
Several object categorization algorithms use kernel methods over multiple cues, as they offer a principled approach to combine multiple cues, and to obtain state-of-theart perform...
Learning to act in a multiagent environment is a difficult problem since the normal definition of an optimal policy no longer applies. The optimal policy at any moment depends on ...
Strictness analysis has been a living field of investigation since Mycroft's original work in 1980, and is getting increasingly significant with the still wider use of lazy fu...
We address covariance estimation under mean-squared loss in the Gaussian setting. Specifically, we consider shrinkage methods which are suitable for high dimensional problems wit...