Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Decision Making with Side Information and Unbounded Loss Functions   We consider the problem of decision-making with side information and
unbounded loss functions. Inspired by probably approximately correct learning
model, we use a slightly different model that incorporates the notion of side
information in a more generic form to make it applicable to a broader class of
applications including parameter estimation and system identification. We
address sufficient conditions for consistent decision-making with exponential
convergence behavior. In this regard, besides a certain condition on the growth
function of the class of loss functions, it suffices that the class of loss
functions be dominated by a measurable function whose exponential Orlicz
expectation is uniformly bounded over the probabilistic model. Decay exponent,
decay constant, and sample complexity are discussed. Example applications to
method of moments, maximum likelihood estimation, and system identification are
illustrated, as well.

15
The categories of this paper are: nucl-ex
28
The categories of this paper are: alg-geom
35
The categories of this paper are: mtrl-th
6
The categories of this paper are: astro-ph
12
The categories of this paper are: nucl-th
18
The categories of this paper are: econ
26
The categories of this paper are: bayes-an
14
The categories of this paper are: math-ph
8
The categories of this paper are: hep-ex
17
The categories of this paper are: q-fin
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The categories of this paper are: solv-int
24
The categories of this paper are: dg-ga
33
The categories of this paper are: plasm-ph
20
The categories of this paper are: acc-phys
7
The categories of this paper are: hep-th
29
The categories of this paper are: funct-an