ICANN
2007
Springer
13 years 11 months ago
2007
Springer
This paper proposes a novel approach for directly tuning the gaussian kernel matrix for one class learning. The popular gaussian kernel includes a free parameter, σ, that requires...
ICANN
2007
Springer
13 years 11 months ago
2007
Springer
Evolutionary multi-objective optimization of spiking neural networks for solving classification problems is studied in this paper. By means of a Paretobased multi-objective geneti...
ICANN
2007
Springer
13 years 11 months ago
2007
Springer
Abstract. We develop a probabilistic interpretation of non-linear component extraction in neural networks that activate their hidden units according to a softmaxlike mechanism. On ...
ICANN
2007
Springer
13 years 11 months ago
2007
Springer
SpikeStream is a new simulator of biologically structured spiking neural networks that can be used to edit, display and simulate up to 100,000 neurons. This simulator uses a combin...
ICANN
2007
Springer
13 years 11 months ago
2007
Springer
ICANN
2007
Springer
13 years 11 months ago
2007
Springer
Abstract. We present a model for the ontogenesis of information routing architectures in the brain based on chemical markers guiding axon growth. The model produces all-to-all conn...
ICANN
2007
Springer
13 years 11 months ago
2007
Springer
The hierarchical non-negative matrix factorization (HNMF) is a multilayer generative network for decomposing strictly positive data into strictly positive activations and base vect...
ICANN
2007
Springer
13 years 11 months ago
2007
Springer
Abstract. We present a novel approach to structure learning for graphical models. By using nonparametric estimates to model clique densities in decomposable models, both discrete a...
ICANN
2007
Springer
13 years 11 months ago
2007
Springer
Radial basis function networks (RBF) are efficient general function approximators. They show good generalization performance and they are easy to train. Due to theoretical consider...
ICANN
2007
Springer
13 years 11 months ago
2007
Springer
Abstract. We present a method to find the exact maximal margin hyperplane for linear Support Vector Machines when a new (existing) component is added (removed) to (from) the inner...