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» Automatic Parameter Learning for Multiple Network Alignment
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ESANN
2001
15 years 1 months ago
Transfer functions: hidden possibilities for better neural networks
Abstract. Sigmoidal or radial transfer functions do not guarantee the best generalization nor fast learning of neural networks. Families of parameterized transfer functions provide...
Wlodzislaw Duch, Norbert Jankowski
MLMI
2004
Springer
15 years 5 months ago
Multistream Dynamic Bayesian Network for Meeting Segmentation
This paper investigates the automatic analysis and segmentation of meetings. A meeting is analysed in terms of individual behaviours and group interactions, in order to decompose e...
Alfred Dielmann, Steve Renals
TNN
2008
181views more  TNN 2008»
14 years 11 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
SWWS
2008
15 years 1 months ago
A Harmony based Adaptive Ontology Mapping Approach
- Ontology mapping seeks to find semantic correspondences between similar elements of different ontologies. Ontology mapping is critical to achieve semantic interoperability in the...
Ming Mao, Yefei Peng, Michael Spring
GECCO
2008
Springer
155views Optimization» more  GECCO 2008»
15 years 23 days ago
Experiments with indexed FOR-loops in genetic programming
We investigated how indexed FOR-loops, such as the ones found in procedural programming languages, can be implemented in genetic programming. We use them to train programs that le...
Gayan Wijesinghe, Victor Ciesielski