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AI
2002
Springer
14 years 9 months ago
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Zhi-Hua Zhou, Jianxin Wu, Wei Tang
ESANN
2008
14 years 11 months ago
A Regularized Learning Method for Neural Networks Based on Sensitivity Analysis
The Sensitivity-Based Linear Learning Method (SBLLM) is a learning method for two-layer feedforward neural networks, based on sensitivity analysis, that calculates the weights by s...
Bertha Guijarro-Berdiñas, Oscar Fontenla-Ro...
IJON
2008
186views more  IJON 2008»
14 years 9 months ago
Computational analysis and learning for a biologically motivated model of boundary detection
In this work we address the problem of boundary detection by combining ideas and approaches from biological and computational vision. Initially, we propose a simple and efficient ...
Iasonas Kokkinos, Rachid Deriche, Olivier D. Fauge...
ICANNGA
2007
Springer
153views Algorithms» more  ICANNGA 2007»
14 years 11 months ago
A Neural Framework for Robot Motor Learning Based on Memory Consolidation
Neural networks are a popular technique for learning the adaptive control of non-linear plants. When applied to the complex control of android robots, however, they suffer from se...
Heni Ben Amor, Shuhei Ikemoto, Takashi Minato, Ber...
CIG
2006
IEEE
14 years 11 months ago
Improving Artificial Intelligence In a Motocross Game
We have previously investigated the use of artificial neural networks to ride simulated motorbikes in a new computer game. These artificial neural networks were trained using two d...
Benoit Chaperot, Colin Fyfe