We show how to use unlabeled data and a deep belief net (DBN) to learn a good covariance kernel for a Gaussian process. We first learn a deep generative model of the unlabeled da...
Visualization of non-vectorial objects is not easy in practice due to their lack of convenient vectorial representation. Representative approaches are Kernel PCA and Kernel Laplac...
In this paper, we present a novel multiple kernel method to learn the optimal classification function for visual concept. Although many carefully designed kernels have been propose...
Tasks of information retrieval depend on a good distance function for measuring similarity between data instances. The most effective distance function must be formulated in a con...
Abstract. Improving accuracy in Information Retrieval tasks via semantic information is a complex problem characterized by three main aspects: the document representation model, th...
Roberto Basili, Marco Cammisa, Alessandro Moschitt...