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» A Boosting Algorithm for Regression
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FGR
2006
IEEE
131views Biometrics» more  FGR 2006»
15 years 10 months ago
Haar Features for FACS AU Recognition
We examined the effectiveness of using Haar features and the Adaboost boosting algorithm for FACS action unit (AU) recognition. We evaluated both recognition accuracy and processi...
Jacob Whitehill, Christian W. Omlin
ECAI
2006
Springer
15 years 8 months ago
A Real Generalization of Discrete AdaBoost
Scaling discrete AdaBoost to handle real-valued weak hypotheses has often been done under the auspices of convex optimization, but little is generally known from the original boost...
Richard Nock, Frank Nielsen
ICONIP
2004
15 years 5 months ago
Outliers Treatment in Support Vector Regression for Financial Time Series Prediction
Recently, the Support Vector Regression (SVR) has been applied in the financial time series prediction. The financial data are usually highly noisy and contain outliers. Detecting ...
Haiqin Yang, Kaizhu Huang, Laiwan Chan, Irwin King...
CORR
2010
Springer
92views Education» more  CORR 2010»
15 years 1 months ago
Regression on fixed-rank positive semidefinite matrices: a Riemannian approach
The paper addresses the problem of learning a regression model parameterized by a fixed-rank positive semidefinite matrix. The focus is on the nonlinear nature of the search space...
Gilles Meyer, Silvere Bonnabel, Rodolphe Sepulchre
BMCBI
2008
136views more  BMCBI 2008»
15 years 4 months ago
Allowing for mandatory covariates in boosting estimation of sparse high-dimensional survival models
Background: When predictive survival models are built from high-dimensional data, there are often additional covariates, such as clinical scores, that by all means have to be incl...
Harald Binder, Martin Schumacher