Multiple kernel learning (MKL) uses a weighted combination of kernels where the weight of each kernel is optimized during training. However, MKL assigns the same weight to a kerne...
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...
Previous Multiple Kernel Learning approaches (MKL) employ different kernels by their linear combination. Though some improvements have been achieved over methods using single kerne...
— Using the classical Parzen window estimate as the target function, the kernel density estimation is formulated as a regression problem and the orthogonal forward regression tec...
This paper presents a study aimed to the realization of a novel
multiresolution registration framework. The transformation
function is computed iteratively as a composition of lo...