Backpropagation, similar to most learning algorithms that can form complex decision surfaces, is prone to overfitting. This work presents classification-based objective functions, ...
Biological brains can adapt and learn from past experience. In neuroevolution, i.e. evolving artificial neural networks (ANNs), one way that agents controlled by ANNs can evolve t...
We present a framework for the modeling of multipath routing in connectionless networks that dynamically adapt to network congestion. The basic routing protocol uses a short-term ...
It is generally believed that by combining several diverse intrusion detectors (i.e., forming an IDS ensemble), we may achieve better performance. However, there has been very lit...
Background: Chow and Liu showed that the maximum likelihood tree for multivariate discrete distributions may be found using a maximum weight spanning tree algorithm, for example K...
David Edwards, Gabriel C. G. de Abreu, Rodrigo Lab...