Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
: Applications such as Face Recognition (FR) that deal with high-dimensional data need a mapping technique that introduces representation of low-dimensional features with enhanced ...
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
In many computer vision tasks like face recognition and image retrieval, one is often confronted with high-dimensional data. Procedures that are analytically or computationally ma...
The choice of a color space is of great importance for many computer vision algorithms (e.g. edge detection and object recognition). It induces the equivalence classes to the actu...