Aggregation via Empirical risk minimization
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Mendelson, Shahar; Lecue, Guillaume
Description
Given a finite set F of estimators, the problem of aggregation is to construct a new estimator whose risk is as close as possible to the risk of the best estimator in F. It was conjectured that empirical minimization performed in the convex hull of F is an optimal aggregation method, but we show that this conjecture is false. Despite that, we prove that empirical minimization in the convex hull of a well chosen, empirically determined subset of F is an optimal aggregation method.
Collections | ANU Research Publications |
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Date published: | 2009 |
Type: | Journal article |
URI: | http://hdl.handle.net/1885/36461 |
Source: | Probability Theory and Related Fields |
DOI: | 10.1007/s00440-008-0180-8 |
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