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BIBM
2008
IEEE
172views Bioinformatics» more  BIBM 2008»
15 years 3 months ago
Boosting Methods for Protein Fold Recognition: An Empirical Comparison
Protein fold recognition is the prediction of protein’s tertiary structure (Fold) given the protein’s sequence without relying on sequence similarity. Using machine learning t...
Yazhene Krishnaraj, Chandan K. Reddy
90
Voted
CVPR
2005
IEEE
15 years 3 months ago
Robust Face Detection with Multi-Class Boosting
With the aim to design a general learning framework for detecting faces of various poses or under different lighting conditions, we are motivated to formulate the task as a classi...
Yen-Yu Lin, Tyng-Luh Liu
NIPS
2000
14 years 10 months ago
Structure Learning in Human Causal Induction
We use graphical models to explore the question of how people learn simple causal relationships from data. The two leading psychological theories can both be seen as estimating th...
Joshua B. Tenenbaum, Thomas L. Griffiths
MICCAI
2008
Springer
15 years 10 months ago
Cortical Surface Thickness as a Classifier: Boosting for Autism Classification
We study the problem of classifying an autistic group from controls using structural image data alone, a task that requires a clinical interview with a psychologist. Because of the...
Vikas Singh, Lopamudra Mukherjee, Moo K. Chung
FOCS
2010
IEEE
14 years 7 months ago
Boosting and Differential Privacy
Boosting is a general method for improving the accuracy of learning algorithms. We use boosting to construct improved privacy-preserving synopses of an input database. These are da...
Cynthia Dwork, Guy N. Rothblum, Salil P. Vadhan