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» Constructive Neural Network Learning Algorithms
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ESWA
2006
165views more  ESWA 2006»
15 years 2 months ago
Optimal ensemble construction via meta-evolutionary ensembles
In this paper we propose a meta-evolutionary approach to improve on the performance of individual classifiers. In the proposed system, individual classifiers evolve, competing to ...
YongSeog Kim, W. Nick Street, Filippo Menczer
DAGSTUHL
2008
15 years 3 months ago
The Grand Challenges and Myths of Neural-Symbolic Computation
The construction of computational cognitive models integrating the connectionist and symbolic paradigms of artificial intelligence is a standing research issue in the field. The co...
Luís C. Lamb
GECCO
2010
Springer
181views Optimization» more  GECCO 2010»
15 years 7 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...
129
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IJCNN
2000
IEEE
15 years 6 months ago
Support Vector Machine for Regression and Applications to Financial Forecasting
The main purpose of this paper is to compare the support vector machine (SVM) developed by Vapnik with other techniques such as Backpropagation and Radial Basis Function (RBF) Net...
Theodore B. Trafalis, Huseyin Ince
ESANN
2006
15 years 3 months ago
Diversity creation in local search for the evolution of neural network ensembles
Abstract. The EENCL algorithm [1] automatically designs neural network ensembles for classification, combining global evolution with local search based on gradient descent. Two mec...
Pete Duell, Iris Fermin, Xin Yao