This work presents a kernel method for clustering the nodes of a weighted, undirected, graph. The algorithm is based on a two-step procedure. First, the sigmoid commute-time kernel...
We study Mercer's theorem and feature maps for several positive definite kernels that are widely used in practice. The smoothing properties of these kernels will also be explo...
Kernel methods yield state-of-the-art performance in certain applications such as image classification and object detection. However, large scale problems require machine learning...
Sreekanth Vempati, Andrea Vedaldi, Andrew Zisserma...
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...