Discriminative learning is challenging when examples are sets of features, and the sets vary in cardinality and lack any sort of meaningful ordering. Kernel-based classification m...
We study the use of kernel subspace methods that learn low-dimensional subspace representations for classification tasks. In particular, we propose a new method called kernel weigh...
We propose in this article an image classification technique based on kernel methods and graphs. Our work explores the possibility of applying marginalized kernels to image process...