General oracle inequalities for model selection
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Date
2009
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Journal Article
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Abstract
Model selection is often performed by empirical risk minimization. The quality of selection in a given situation can be assessed by risk bounds, which require assumptions both on the margin and the tails of the losses used. Starting with examples from the 3 basic estimation problems, regression, classification and density estimation, we formulate risk bounds for empirical risk minimization and prove them at a very general level, for general margin and power tail behavior of the excess losses. These bounds we then apply to typical examples.
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published
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Volume
3
Pages / Article No.
176 - 204
Publisher
Cornell University
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03717 - van de Geer, Sara (emeritus) / van de Geer, Sara (emeritus)