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Abstract: We study L 2 Boosting and propose a new alternative version which employs modelselection criteria (MS-L 2 Boosting). For the special case of an orthogonal linear model, we give an algorithmical equivalence of L 2 Boosting to the Lasso and of one new MS- L 2 Boosting to Breiman's nonnegative garrote estimator. (Update)
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BibTeX entry: (Update)
@misc{ hlmann-boosting,
author = "Peter Bühlmann and Bin Yu",
title = "Boosting, Model Selection, Lasso and Nonnegative Garrote",
url = "citeseer.ist.psu.edu/757058.html" }
Citations (may not include all citations):657 Bagging predictors - Breiman - 1996
500 Experiments with a new boosting algorithm - Freund, Schapire - 1996
273 Multivariate adaptive regression splines (context) - Friedman - 1991
260 Matching pursuits with time-frequency dictionaries - Mallat, Zhang - 1993
236 Additive logistic regression: a statistical view of boosting - Friedman, Hastie et al. - 2000
214 Information theory and an extension of the maximum likelihoo.. (context) - Akaike - 1973
202 Ideal spatial adaptation by wavelet shrinkage - Donoho, Johnstone - 1994
176 Exploratory data analysis (context) - Tukey - 1977
161 Nonparametric Regression and Generalized Linear Models (context) - Green, Silverman - 1994
90 Estimating the dimension of a model (context) - Schwartz - 1978
83 Regression shrinkage and selection via the lasso - Tibshirani - 1996
61 Greedy function approximation: a gradient boosting machine - Friedman - 2001
41 A new look at the statistical model identi cation (context) - Akaike - 1974
35 An optimal selection of regression variables (context) - Shibata - 1981
29 Regression and time series model selection in small samples (context) - Hurvich, Tsai - 1989
23 Process consistency for AdaBoost - Jiang - 2004
22 Smoothing parameter selection in nonparametric regression us.. (context) - Hurvich, Simono et al. - 1998
21 Arcing classi ers (context) - Breiman - 1998
20 Least angle regression - Efron, Hastie et al. - 2004
14 Better subset regression using the nonnegative garrote (context) - Breiman - 1995
14 the Bayes-risk consistency of regularized boosting methods - Lugosi, Vayatis - 2004
13 Model selection and minimum description length principle (context) - Hansen, Yu - 2001
10 Model selection and prediction: normal regression (context) - Speed, Yu - 1994
8 Boosting with early stopping: convergence and consistency - Zhang, Yu - 2003
5 Boosting with the L 2 loss: regression and classi cation (context) - uhlmann, Yu - 2003
5 Statistical predictor identi cation (context) - Akaike - 1970
2 Boosting for high-dimensional linear models (context) - uhlmann - 2004
2 and Zhang (context) - Mannor, Meir - 2002
1 On nonnegative garrote estimator in a linear regression mode.. (context) - Mohammadi, van de - 2002
1 Discussion on \Least angle regression - Madigan, Ridgeway - 2004
1 Boosted lasso and reverse boosting (context) - Zhao, Yu - 2004
1 Further analyses of the data by Akaike's information criteri.. (context) - Sugiura - 1978
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