Similarity matrices generated from many applications may not be positive semidefinite, and hence can't fit into the kernel machine framework. In this paper, we study the prob...
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and different r...
Choon Hui Teo, Alex J. Smola, S. V. N. Vishwanatha...
Kernels are two-placed functions that can be interpreted as inner products in some Hilbert space. It is this property which makes kernels predestinated to carry linear models of l...
— Category Ranking is a variant of the multi-label classification problem, in which, rather than performing a (hard) assignment to an object of categories from a predefined set...
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...