Mutation-based Evolutionary Algorithms, also known as Evolutionary Programming (EP) are commonly applied to Artificial Neural Networks (ANN) parameters optimization. This paper pre...
Kristina Davoian, Alexander Reichel, Wolfram-Manfr...
We develop improved risk bounds for function estimation with models such as single hidden layer neural nets, using a penalized least squares criterion to select the size of the mod...
An automatic recognition of online handwritten text has been an on-going research problem for nearly four decades. It has been gaining more interest due to the increasing populari...
We present a novel approach to dealing with overfitting in black-box models. It is based on the leverages of the samples, i.e. on the influence that each observation has on the pa...
In this paper we explore the model–building issue of multiobjective optimization estimation of distribution algorithms. We argue that model–building has some characteristics t...