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TNN
2008
181views more  TNN 2008»
13 years 9 months ago
Optimized Approximation Algorithm in Neural Networks Without Overfitting
In this paper, an optimized approximation algorithm (OAA) is proposed to address the overfitting problem in function approximation using neural networks (NNs). The optimized approx...
Yinyin Liu, Janusz A. Starzyk, Zhen Zhu
ESANN
2006
13 years 10 months ago
Diversity creation in local search for the evolution of neural network ensembles
Abstract. The EENCL algorithm [1] automatically designs neural network ensembles for classification, combining global evolution with local search based on gradient descent. Two mec...
Pete Duell, Iris Fermin, Xin Yao
BC
2007
107views more  BC 2007»
13 years 9 months ago
Decoding spike train ensembles: tracking a moving stimulus
We consider the issue of how to read out the information from nonstationary spike train ensembles. Based on the theory of censored data in statistics, we propose a ‘censored’ m...
Enrico Rossoni, Jianfeng Feng
IJCAI
1997
13 years 10 months ago
An Effective Learning Method for Max-Min Neural Networks
Max and min operations have interesting properties that facilitate the exchange of information between the symbolic and real-valued domains. As such, neural networks that employ m...
Loo-Nin Teow, Kia-Fock Loe
ICAISC
2010
Springer
13 years 11 months ago
Computer Assisted Peptide Design and Optimization with Topology Preserving Neural Networks
Abstract. We propose a non-standard neural network called TPNN which offers the direct mapping from a peptide sequence to a property of interest in order to model the quantitative ...
Jörg D. Wichard, Sebastian Bandholtz, Carsten...