Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A tractable ellipsoidal approximation for voltage regulation problems   We present a machine learning approach to the solution of chance constrained
optimizations in the context of voltage regulation problems in power system
operation. The novelty of our approach resides in approximating the feasible
region of uncertainty with an ellipsoid. We formulate this problem using a
learning model similar to Support Vector Machines (SVM) and propose a sampling
algorithm that efficiently trains the model. We demonstrate our approach on a
voltage regulation problem using standard IEEE distribution test feeders.

4
The categories of this paper are: cond-mat
19
The categories of this paper are: eess
15
The categories of this paper are: nucl-ex
22
The categories of this paper are: chao-dyn
28
The categories of this paper are: alg-geom
37
The categories of this paper are: supr-con
3
The categories of this paper are: physics
31
The categories of this paper are: ao-sci
5
The categories of this paper are: gr-qc
29
The categories of this paper are: funct-an
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The categories of this paper are: hep-ph
34
The categories of this paper are: chem-ph
36
The categories of this paper are: cmp-lg
18
The categories of this paper are: econ
32
The categories of this paper are: atom-ph
6
The categories of this paper are: astro-ph