Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Heteroscedasticity-aware residuals-based contextual stochastic
  optimization   We explore generalizations of some integrated learning and optimization
frameworks for data-driven contextual stochastic optimization that can adapt to
heteroscedasticity. We identify conditions on the stochastic program, data
generation process, and the prediction setup under which these generalizations
possess asymptotic and finite sample guarantees for a class of stochastic
programs, including two-stage stochastic mixed-integer programs with continuous
recourse. We verify that our assumptions hold for popular parametric and
nonparametric regression methods.

8
The categories of this paper are: hep-ex
26
The categories of this paper are: bayes-an
31
The categories of this paper are: ao-sci
34
The categories of this paper are: chem-ph
32
The categories of this paper are: atom-ph
20
The categories of this paper are: acc-phys
25
The categories of this paper are: patt-sol
28
The categories of this paper are: alg-geom
1
The categories of this paper are: cs
10
The categories of this paper are: q-bio
18
The categories of this paper are: econ
35
The categories of this paper are: mtrl-th
12
The categories of this paper are: nucl-th
24
The categories of this paper are: dg-ga
6
The categories of this paper are: astro-ph
36
The categories of this paper are: cmp-lg