Application of machine learning techniques to optical communication systems and networks

The recent exponential growing of machine learning techniques (data-mining, deep-learning, manifold learning, linear and nonlinear regression techniques ... to cite but a few) makes

We present and evaluate our semantic profiling architecture in four ways: (1) the perfor- mance of the Tag Filtering and mapping to Wikipedia entries, (2) the difference between

This presents benefits for the practical use of GT in MDE, as it allows: (i) to automatically derive pre-conditions from the meta-model integrity constraints, ensuring rule

Table 1 shows a summary, gathering the two typical scenarios for DSTLs (DSTLs built in an ad-hoc way, and families of similar transformation tasks), whether the source or

A meta-model concept is a specification of the minimal requirements that a meta- model should fulfil to qualify for the source or target domain of a generic model-

This time is almost 150 times higher than that required by the proposed method (0.03 s). The results corresponding to the pre- conditioned Tikhonov regularization method were

In fact, data mining techniques have already been used in E-learning systems, but most of the times their application is oriented to provide better support to students; little work

This project is going to focus on the design, implementation and analysis of a new machine learning model based on decision trees and other models, specifically neural networks..