Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning by mirror averaging   Given a finite collection of estimators or classifiers, we study the problem
of model selection type aggregation, that is, we construct a new estimator or
classifier, called aggregate, which is nearly as good as the best among them
with respect to a given risk criterion. We define our aggregate by a simple
recursive procedure which solves an auxiliary stochastic linear programming
problem related to the original nonlinear one and constitutes a special case of
the mirror averaging algorithm. We show that the aggregate satisfies sharp
oracle inequalities under some general assumptions. The results are applied to
several problems including regression, classification and density estimation.

18
The categories of this paper are: econ
23
The categories of this paper are: solv-int
31
The categories of this paper are: ao-sci
6
The categories of this paper are: astro-ph
35
The categories of this paper are: mtrl-th
4
The categories of this paper are: cond-mat
34
The categories of this paper are: chem-ph
22
The categories of this paper are: chao-dyn
17
The categories of this paper are: q-fin
9
The categories of this paper are: nlin
3
The categories of this paper are: physics
36
The categories of this paper are: cmp-lg
14
The categories of this paper are: math-ph
19
The categories of this paper are: eess
27
The categories of this paper are: comp-gas
11
The categories of this paper are: hep-lat