We introduce a regularized kernel-based rule for unsupervised change detection based on a simpler version of the recently proposed kernel Fisher discriminant ratio. Compared to ot...
Blind blur identification in video sequences becomes more important. This paper presents a new method for identifying parameters of different blur kernels and image restoration in ...
We study the connection between higher order total variation (TV) regularization and support vector regression (SVR) with spline kernels in a one-dimensional discrete setting. We p...
The support vector machine (SVM) is a widely used tool for classification. Many efficient implementations exist for fitting a two-class SVM model. The user has to supply values fo...
Trevor Hastie, Saharon Rosset, Robert Tibshirani, ...
We equate nonlinear dimensionality reduction (NLDR) to graph embedding with side information about the vertices, and derive a solution to either problem in the form of a kernel-ba...