We propose a new family of latent variable models called max-margin min-entropy (m3e) models, which define a distribution over the output and the hidden variables conditioned on ...
Kevin Miller, M. Pawan Kumar, Benjamin Packer, Dan...
Abstract. This paper reports our comparative evaluation of three machine learning methods on Chinese text categorization. Whereas a wide range of methods have been applied to Engli...
Kernel machines rely on an implicit mapping of the data such that non-linear classification in the original space corresponds to linear classification in the new space. As kernel ...
We propose a local, generative model for similarity-based classification. The method is applicable to the case that only pairwise similarities between samples are available. The c...
The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Mul...
Marie Szafranski, Yves Grandvalet, Alain Rakotomam...