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ESSMAC
2003
Springer
15 years 11 months ago
Nonlinear Predictive Control with a Gaussian Process Model
Abstract. Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. The Gaussian processes can h...
Jus Kocijan, Roderick Murray-Smith
GECCO
2003
Springer
124views Optimization» more  GECCO 2003»
15 years 11 months ago
Using an Immune System Model to Explore Mate Selection in Genetic Algorithms
Abstract. When Genetic Algorithms (GAs) are employed in multimodal function optimization, engineering and machine learning, identifying multiple peaks and maintaining subpopulation...
Chien-Feng Huang
GECCO
2010
Springer
181views Optimization» more  GECCO 2010»
15 years 11 months ago
Evolving neural networks in compressed weight space
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...
Jan Koutnik, Faustino J. Gomez, Jürgen Schmid...
AUSAI
2001
Springer
15 years 10 months ago
Wrapping Boosters against Noise
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...
EUROGP
2001
Springer
15 years 10 months ago
A GP Artificial Ant for Image Processing: Preliminary Experiments with EASEA
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...