We explore generic mechanisms to introduce structural hints into the method of Unsupervised Kernel Regression (UKR) in order to learn representations of data sequences in a semi-su...
Jan Steffen, Stefan Klanke, Sethu Vijayakumar, Hel...
Background: Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks ...
Peter Meinicke, Maike Tech, Burkhard Morgenstern, ...
An adaptive ADER finite volume method on unstructured meshes is proposed. The method combines high order polyharmonic spline WENO reconstruction with high order flux evaluation. Po...
Terhemen Aboiyar, Emmanuil H. Georgoulis, Armin Is...
We propose an online anomal movement detection method using incremental unsupervised learning. As the feature for discrimination, we extract the principal component of the spatio-...
Inspired by co-training, many multi-view semi-supervised kernel methods implement the following idea: find a function in each of multiple Reproducing Kernel Hilbert Spaces (RKHSs)...