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IJON
2007
184views more  IJON 2007»
15 years 1 months ago
Convex incremental extreme learning machine
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
Guang-Bin Huang, Lei Chen
VLSISP
2002
124views more  VLSISP 2002»
15 years 1 months ago
Agglomerative Learning Algorithms for General Fuzzy Min-Max Neural Network
In this paper two agglomerative learning algorithms based on new similarity measures defined for hyperbox fuzzy sets are proposed. They are presented in a context of clustering and...
Bogdan Gabrys
DMIN
2006
126views Data Mining» more  DMIN 2006»
15 years 3 months ago
Comparison and Analysis of Mutation-based Evolutionary Algorithms for ANN Parameters Optimization
Mutation-based Evolutionary Algorithms, also known as Evolutionary Programming (EP) are commonly applied to Artificial Neural Networks (ANN) parameters optimization. This paper pre...
Kristina Davoian, Alexander Reichel, Wolfram-Manfr...
NPL
2000
99views more  NPL 2000»
15 years 1 months ago
On the Internal Representations of Product Units
This paper explores internal representation power of product units [1] that act as the functional nodes in the hidden layer of a multi-layer feedforward network. Interesting proper...
Jung-Hua Wang, Yi-Wei Yu, Jia-Horng Tsai
ICANN
2001
Springer
15 years 6 months ago
The Bayesian Committee Support Vector Machine
Empirical evidence indicates that the training time for the support vector machine (SVM) scales to the square of the number of training data points. In this paper, we introduce the...
Anton Schwaighofer, Volker Tresp