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GECCO
2009
Springer
122views Optimization» more  GECCO 2009»
15 years 11 months ago
Visualising random boolean network dynamics
We propose a simple approach to visualising the time behaviour of Random Boolean Networks (RBNs), and demonstrate the approach by examining the effect of canalising functions for ...
Susan Stepney
GECCO
2010
Springer
197views Optimization» more  GECCO 2010»
15 years 11 months ago
Niching the CMA-ES via nearest-better clustering
We investigate how a niching based evolutionary algorithm fares on the BBOB function test set, knowing that most problems are not very well suited to this algorithm class. However...
Mike Preuss
NIPS
2007
15 years 9 months ago
Convex Learning with Invariances
Incorporating invariances into a learning algorithm is a common problem in machine learning. We provide a convex formulation which can deal with arbitrary loss functions and arbit...
Choon Hui Teo, Amir Globerson, Sam T. Roweis, Alex...
EUSFLAT
2003
121views Fuzzy Logic» more  EUSFLAT 2003»
15 years 8 months ago
An adaptive learning algorithm for a neo fuzzy neuron
In the paper, a new optimal learning algorithm for a neo-fuzzy neuron (NFN) is proposed. The algorithm is characteristic in that it provides online tuning of not only the synaptic...
Yevgeniy Bodyanskiy, Illya Kokshenev, Vitaliy Kolo...
ICASSP
2010
IEEE
15 years 7 months ago
Generalized Discrete Fourier Transform with optimum correlations
— In this paper, we present design methods to optimize nonlinear phase functions of Generalized DFT (GDFT) for minimized auto and cross correlations. It is shown that GDFT offers...
Ali N. Akansu, Handan Agirman-Tosun