In this paper we present application of genetic programming (GP) [1] to evolution of indirect encoding of neural network weights. We compare usage of original HyperNEAT algorithm w...
A genetic programming method is investigated for optimizing both the architecture and the connection weights of multilayer feedforward neural networks. The genotype of each networ...
A novel method to improve the generalization performance of the Minimum Classification Error (MCE) / Generalized Probabilistic Descent (GPD) learning is proposed. The MCE/GPD learn...
This paper proposes a new connectionist approach to numeric law discovery; i.e., neural networks (law-candidates) are trained by using a newly invented second-order learning algor...
— A new tendency in the design of modern signal processing methods is the creation of hybrid algorithms. This paper gives an overview of different signal processing algorithms si...
Piotr Wilinski, Basel Solaiman, A. Hillion, W. Cza...