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» Learning Models for Predicting Recognition Performance
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BMCBI
2008
147views more  BMCBI 2008»
15 years 3 months ago
Transmembrane helix prediction using amino acid property features and latent semantic analysis
Background: Prediction of transmembrane (TM) helices by statistical methods suffers from lack of sufficient training data. Current best methods use hundreds or even thousands of f...
Madhavi Ganapathiraju, Narayanas Balakrishnan, Raj...
ICANN
2009
Springer
15 years 7 months ago
Profiling of Mass Spectrometry Data for Ovarian Cancer Detection Using Negative Correlation Learning
This paper proposes a novel Mass Spectrometry data profiling method for ovarian cancer detection based on negative correlation learning (NCL). A modified Smoothed Nonlinear Energy ...
Shan He, Huanhuan Chen, Xiaoli Li, Xin Yao
118
Voted
BMCBI
2007
121views more  BMCBI 2007»
15 years 3 months ago
Predicting zinc binding at the proteome level
Background: Metalloproteins are proteins capable of binding one or more metal ions, which may be required for their biological function, for regulation of their activities or for ...
Andrea Passerini, Claudia Andreini, Sauro Menchett...
109
Voted
MVA
2007
15 years 4 months ago
Semi-supervised Incremental Learning of Manipulative Tasks
For a social robot, the ability of learning tasks via human demonstration is very crucial. But most current approaches suffer from either the demanding of the huge amount of label...
Zhe Li, Sven Wachsmuth, Jannik Fritsch, Gerhard Sa...
134
Voted
ECAI
2004
Springer
15 years 8 months ago
Towards Efficient Learning of Neural Network Ensembles from Arbitrarily Large Datasets
Advances in data collection technologies allow accumulation of large and high dimensional datasets and provide opportunities for learning high quality classification and regression...
Kang Peng, Zoran Obradovic, Slobodan Vucetic