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In modern data analysis, sparse model selection becomes inevitable once the number of predictors variables is very high.
A universal data compression system
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F. R. Bach · 2008
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Model selection through sparse maximum likelihood estimation for multivariate gaussian or binary data
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R. Dezeure, P. Bühlmann, L. Meier, and N. Meinshausen · 2015
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B. Hofner, L. Boccuto, and M. Göker · 2015
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Measuring the stability of feature selection
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Robust distributed multi-speaker voice activity detection using stability selection for sparse non-negative feature extraction
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stabs: Stability Selection with Error Control , 2017
B. Hofner and T. Hothorn · 2017
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T. Hothorn, P. Bühlmann, T. Kneib, M. Schmid, and B. Hofner · 2010
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mboost: Model-Based Boosting , 2017
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High-dimensional regression in practice: an empirical study of finite-sample prediction, variable selection and ranking
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