We study the extent to which xing the second layer weights reduces the capacity and generalization ability of a two-layer perceptron. Architectures with N inputs, K hidden units and a single output are considered, with both overlapping and non-overlapping receptive elds. We obtain from simulations one measure of the strength of a network-its critical capacity, c. Using the ansatz med / (c ?) ?2...

Microarray data analysis and classification has demonstrated convincingly that it provides an effective methodology for the effective diagnosis of diseases and cancers. Although much research has been performed on applying machine learning techniques for microarray data classification during the past years, it has been shown that conventional machine learning techniques have intrinsic drawbacks...

This paper describes a coupling between a real NC control unit and a virtual machine and its application potentials for vocational training. First the Hardware-in-the-Loop coupling, including the setup of the machine model, the connection itself and the realized material removal process, is described. Based on that, possible application scenarios for vocational training are discussed. In additi...

The classification of subjects' pathologies enables a rigorousness to be applied to the treatment of certain pathologies, as doctors on occasions play with so many variables that they can end up confusing some illnesses with others. Thanks to Machine Learning techniques applied to a health-record database, it is possible to make using our algorithm. hClass contains a non-linear classification o...

The beginnings of machine translation in Canada can be dated to 1965: that year while the ALPAC committee was preparing the infamous report that would decimate MT around the world for years to come, the National Research Council of Canada blithely decided to fund two machine translation projects, one at the University of Saskatchewan and the other at the University of Montreal. The Saskatchewan...

In this paper we consider large scale distributed committee machines where no local data exchange is possible between neural network modules. Regularization neural networks are used for both the modules as well as the combiner committee in an embedded architecture. After the committee training no module will know anything else except its own local data. This privacy preserving obligation is a c...

One of the necessary tasks of a machine translation system is lexical transfer. In some cases there is a one-to-one mapping from source language word to target language word. What theoretical model is followed when there is a one-to-many mapping? Unfortunately, none of the linguistic models that have been used in machine translation include a lexical transfer component. In the absence of a theo...

We consider the problem of on-line gradient descent learning for general two-layer neural networks. An analytic solution is presented and used to investigate the role of the learning rate in controlling the evolution and convergence of the learning process. Learning in layered neural networks refers to the modification of internal parameters {J} which specify the strength of the interneuron cou...