Graph kernels methods are based on an implicit embedding of graphs within a vector space of large dimension. This implicit embedding allows to apply to graphs methods which where u...
In this paper, we compare two different approaches for semiautomatic detection of skin hyper-pigmentation on multispectral images. These two methods are support vector machine (SV...
In this paper we propose a new information-theoretic divisive algorithm for word clustering applied to text classification. In previous work, such "distributional clustering&...
Inderjit S. Dhillon, Subramanyam Mallela, Rahul Ku...
Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we co...
Abstract. We present a survey of recent results concerning the theoretical and empirical performance of algorithms for learning regularized least-squares classifiers. The behavior ...