Weighted graph regularization provides a rich framework that allows to regularize functions defined over the vertices of a weighted graph. Until now, such a framework has been only...
This paper addresses the problem of category-level image classification. The underlying image model is a graph whose nodes correspond to a dense set of regions, and edges reflec...
In this paper we present a statistical learning scheme for image classification based on a mixture of old fashioned ideas and state of the art learning tools. We represent input i...
This paper investigates the use of a one-class support vector machine algorithm to detect the onset of system anomalies, and trend output classification probabilities, as a way to ...
The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...