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» An Effective Learning Method for Max-Min Neural Networks
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PRL
2011
14 years 11 months ago
Efficient approximate Regularized Least Squares by Toeplitz matrix
Machine Learning based on the Regularized Least Square (RLS) model requires one to solve a system of linear equations. Direct-solution methods exhibit predictable complexity and s...
Sergio Decherchi, Paolo Gastaldo, Rodolfo Zunino
JMLR
2012
13 years 6 months ago
Random Search for Hyper-Parameter Optimization
Grid search and manual search are the most widely used strategies for hyper-parameter optimization. This paper shows empirically and theoretically that randomly chosen trials are ...
James Bergstra, Yoshua Bengio
IJCNN
2007
IEEE
15 years 10 months ago
The Metro Visualisation of Component Planes for Self-Organising Maps
— The Self-Organising Map is a popular unsupervised neural network model which has successfully been used for clustering various kinds of data. To help in understanding the infl...
Robert Neumayer, Rudolf Mayer, Georg Pölzlbau...
ICANN
2001
Springer
15 years 8 months ago
Independent Variable Group Analysis
Humans tend to group together related properties in order to understand complex phenomena. When modeling large problems with limited representational resources, it is important to...
Krista Lagus, Esa Alhoniemi, Harri Valpola
NN
2010
Springer
183views Neural Networks» more  NN 2010»
15 years 2 months ago
Dimensionality reduction for density ratio estimation in high-dimensional spaces
The ratio of two probability density functions is becoming a quantity of interest these days in the machine learning and data mining communities since it can be used for various d...
Masashi Sugiyama, Motoaki Kawanabe, Pui Ling Chui