We compute a common feature selection or kernel selection configuration for multiple support vector machines (SVMs) trained on different yet inter-related datasets. The method is ...
We introduce a new algorithm for binary classification in the selective sampling protocol. Our algorithm uses Regularized Least Squares (RLS) as base classifier, and for this reas...
We extend Support Vector Machines to input spaces that are sets by ensuring that the classifier is invariant to permutations of subelements within each input. Such permutations in...
This paper proposes an automated web site evaluation approach using machine learning to cope with ranking problems. Evaluating web sites is a significant task for web service beca...
Multi-view algorithms, such as co-training and co-EM, utilize unlabeled data when the available attributes can be split into independent and compatible subsets. Co-EM outperforms ...