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» Algorithm Selection using Reinforcement Learning
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171
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ICPR
2006
IEEE
1292views computer vision» more  ICPR 2006»
16 years 3 months ago
Learning-Based License Plate Detection Using Global and Local Features
This paper proposes a license plate detection algorithm using both global statistical features and local Haar-like features. Classifiers using global statistical features are cons...
Huaifeng Zhang, Qiang Wu, Wenjing Jia, Xiangjian H...
KDD
2010
ACM
310views Data Mining» more  KDD 2010»
15 years 6 months ago
An integrated machine learning approach to stroke prediction
Stroke is the third leading cause of death and the principal cause of serious long-term disability in the United States. Accurate prediction of stroke is highly valuable for early...
Aditya Khosla, Yu Cao, Cliff Chiung-Yu Lin, Hsu-Ku...
147
Voted
COLT
2010
Springer
15 years 19 days ago
Active Learning on Trees and Graphs
We investigate the problem of active learning on a given tree whose nodes are assigned binary labels in an adversarial way. Inspired by recent results by Guillory and Bilmes, we c...
Nicolò Cesa-Bianchi, Claudio Gentile, Fabio...
121
Voted
WIOPT
2005
IEEE
15 years 8 months ago
NEURAL: A Self-Organizing Routing Algorithm for Ad Hoc Networks
This paper evaluates a self-organizing routing protocol for Ad Hoc network, called the NEUron Routing ALgorithm (NEURAL). NEURAL has been designed taking into account the learning...
Vicente E. Mujica V, Dorgham Sisalem, Radu Popescu...
ICMLA
2008
15 years 4 months ago
Predicting Algorithm Accuracy with a Small Set of Effective Meta-Features
We revisit 26 meta-features typically used in the context of meta-learning for model selection. Using visual analysis and computational complexity considerations, we find 4 meta-f...
Jun Won Lee, Christophe G. Giraud-Carrier