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GECCO
2004
Springer
116views Optimization» more  GECCO 2004»
14 years 1 months ago
Reducing Fitness Evaluations Using Clustering Techniques and Neural Network Ensembles
Abstract. In many real-world applications of evolutionary computation, it is essential to reduce the number of fitness evaluations. To this end, computationally efficient models c...
Yaochu Jin, Bernhard Sendhoff
NECO
2007
108views more  NECO 2007»
13 years 7 months ago
Spike-Frequency Adapting Neural Ensembles: Beyond Mean Adaptation and Renewal Theories
We propose a Markov process model for spike-frequency adapting neural ensembles which synthesizes existing mean-adaptation approaches, population density methods, and inhomogeneou...
Eilif Mueller, Lars Buesing, Johannes Schemmel, Ka...
BMCBI
2004
205views more  BMCBI 2004»
13 years 7 months ago
A combinational feature selection and ensemble neural network method for classification of gene expression data
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma
ICONIP
2007
13 years 9 months ago
Ensemble Neural Networks with Novel Gene-Subsets for Multiclass Cancer Classification
Multiclass gene selection and classification of cancer are rapidly gaining attention in recent years, while conventional rank-based gene selection methods depend on predefined idea...
Jin-Hyuk Hong, Sung-Bae Cho
IJCNN
2007
IEEE
14 years 2 months ago
Neural Network Ensembles for Time Series Prediction
— Rapidly evolving businesses generate massive amounts of time-stamped data sequences and defy a demand for massively multivariate time series analysis. For such data the predict...
Dymitr Ruta, Bogdan Gabrys