Automatic visual categorization is critically dependent on labeled examples for supervised learning. As an alternative to traditional expert labeling, social-tagged multimedia is ...
This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
Graph representations of data are increasingly common. Such representations arise in a variety of applications, including computational biology, social network analysis, web applic...
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
We present a new generalization bound where the use of unlabeled examples results in a better ratio between training-set size and the resulting classifier’s quality and thus red...