Neural learning using AdaBoost

Proceedings of the International Joint Conference on Neural Networks

Volumn 2, Issue , 2001, Pages 1037-1042

  Murphey, Y L ^a   Chen, Z H ^a   Guo, H ^a  

^a UNIVERSITY OF MICHIGAN DEARBORN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE SYSTEMS; BACKPROPAGATION; ITERATIVE METHODS; LEARNING ALGORITHMS; LEARNING SYSTEMS; PROBABILITY DENSITY FUNCTION; PROBABILITY DISTRIBUTIONS;

ADAPTIVE BOOSTING; GENERALIZATION ABILITY CHALLENGE; NEURAL LEARNING;

NEURAL NETWORKS;

EID: 0034870015     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

1. The sample complexity of pattern classification with neural networks: The size of the weights is more important than the size of the neural network
2. Boosting decision tress
3. Improving generalization performance using double backpropagation
4. A decision-theoretic generalization of on-line learning and an application to boosting
5. The basic ideas in neural networks
6. Boosting the margin: A new explanation for the effectiveness of voting methods
7. A brief introduction to boosting
8. Theoretical views of boosting and applications
9. Adaptive boosting of neural networks for character recognition