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GECCO
2000
Springer
120views Optimization» more  GECCO 2000»
13 years 11 months ago
A Note on Learning and Evolution in Neural Networks
Interactions between evolution and lifetime learning are of great interest to studies of adaptive behaviour both in the natural world and the field of evolutionary computation. Th...
Brian Carse, Johan Oreland
ML
2007
ACM
192views Machine Learning» more  ML 2007»
13 years 7 months ago
Annealing stochastic approximation Monte Carlo algorithm for neural network training
We propose a general-purpose stochastic optimization algorithm, the so-called annealing stochastic approximation Monte Carlo (ASAMC) algorithm, for neural network training. ASAMC c...
Faming Liang
ICANN
2009
Springer
13 years 5 months ago
Mining Rules for the Automatic Selection Process of Clustering Methods Applied to Cancer Gene Expression Data
Different algorithms have been proposed in the literature to cluster gene expression data, however there is no single algorithm that can be considered the best one independently on...
André C. A. Nascimento, Ricardo Bastos Cava...
ECAI
2004
Springer
14 years 28 days ago
Towards Efficient Learning of Neural Network Ensembles from Arbitrarily Large Datasets
Advances in data collection technologies allow accumulation of large and high dimensional datasets and provide opportunities for learning high quality classification and regression...
Kang Peng, Zoran Obradovic, Slobodan Vucetic
IJCNN
2006
IEEE
14 years 1 months ago
Generalization Improvement in Multi-Objective Learning
— Several heuristic methods have been suggested for improving the generalization capability in neural network learning, most of which are concerned with a single-objective (SO) l...
Lars Gräning, Yaochu Jin, Bernhard Sendhoff