We study how the error of an ensemble regression estimator can be decomposed into two components: one accounting for the individual errors and the other accounting for the correlat...
We study the distribution of the statistics `number of fixed points' and `number of excedances' in permutations avoiding subsets of patterns of length 3. We solve all th...
The quadratic discriminant (QD) classifier has proved to be simple and effective in many pattern recognition problems. However, it requires the computation of the inverse of the sa...
Abstract. Semi-supervised learning and ensemble learning are two important learning paradigms. The former attempts to achieve strong generalization by exploiting unlabeled data; th...
We introduce a mechanism for constructing and training a hybrid architecture of projection based units and radial basis functions. In particular, we introduce an optimization sche...