Regularized kernel discriminant analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. Its performance depends on the selection of kernel...
Abstract We review the evolution of the nonparametric regression modeling in imaging from the local Nadaraya-Watson kernel estimate to the nonlocal means and further to transform-d...
Vladimir Katkovnik, Alessandro Foi, Karen Egiazari...
Similarity matrices generated from many applications may not be positive semidefinite, and hence can't fit into the kernel machine framework. In this paper, we study the prob...
1 A kernel determines the inductive bias of a learning algorithm on a specific data set, and it is beneficial to design specific kernel for a given data set. In this work, we propo...
Our objective is to obtain a state-of-the art object category
detector by employing a state-of-the-art image classifier
to search for the object in all possible image subwindows....
Andrea Vedaldi, Varun Gulshan, Manik Varma, Andrew...