This paper proposes a semi-supervised boosting approach to improve statistical word alignment with limited labeled data and large amounts of unlabeled data. The proposed approach ...
The stochastic discrimination (SD) theory considers learning as building models of uniform coverage over data distributions. Despite successful trials of the derived SD method in s...
We address the problem of Bayesian estimation where the statistical relation between the signal and measurements is only partially known. We propose modeling partial Baysian knowl...
Aging has considerable visual effects on the human face and is difficult to simulate using a universally-applicable global model. In this paper, we focus on the hypothesis that th...
The use of multilayer perceptrons (MLP) with threshold functions (binary step function activations) greatly reduces the complexity of the hardware implementation of neural networks...
Vassilis P. Plagianakos, George D. Magoulas, Micha...