Abstract. Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. The Gaussian processes can h...
Abstract. When Genetic Algorithms (GAs) are employed in multimodal function optimization, engineering and machine learning, identifying multiple peaks and maintaining subpopulation...
We propose a new indirect encoding scheme for neural networks in which the weight matrices are represented in the frequency domain by sets of Fourier coefficients. This scheme exp...
Abstract. Wrappers have recently been used to obtain parameter optimizations for learning algorithms. In this paper we investigate the use of a wrapper for estimating the correct n...
Bernhard Pfahringer, Geoffrey Holmes, Gabi Schmidb...
This paper describes how animat-based “food foraging” techniques may be applied to the design of low-level image processing algorithms. First, we show how we implemented the fo...
Enzo Bolis, Christian Zerbi, Pierre Collet, Jean L...