Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Stochastic optimization methods for the simultaneous control of
  parameter-dependent systems   We address the application of stochastic optimization methods for the
simultaneous control of parameter-dependent systems. In particular, we focus on
the classical Stochastic Gradient Descent (SGD) approach of Robbins and Monro,
and on the recently developed Continuous Stochastic Gradient (CSG) algorithm.
We consider the problem of computing simultaneous controls through the
minimization of a cost functional defined as the superposition of individual
costs for each realization of the system. We compare the performances of these
stochastic approaches, in terms of their computational complexity, with those
of the more classical Gradient Descent (GD) and Conjugate Gradient (CG)
algorithms, and we discuss the advantages and disadvantages of each
methodology. In agreement with well-established results in the machine learning
context, we show how the SGD and CSG algorithms can significantly reduce the
computational burden when treating control problems depending on a large amount
of parameters. This is corroborated by numerical experiments.

11
The categories of this paper are: hep-lat
15
The categories of this paper are: nucl-ex
13
The categories of this paper are: quant-ph
29
The categories of this paper are: funct-an
18
The categories of this paper are: econ
8
The categories of this paper are: hep-ex
25
The categories of this paper are: patt-sol
0
The categories of this paper are: hep-ph
9
The categories of this paper are: nlin
4
The categories of this paper are: cond-mat
21
The categories of this paper are: adap-org
26
The categories of this paper are: bayes-an
14
The categories of this paper are: math-ph
23
The categories of this paper are: solv-int
1
The categories of this paper are: cs
19
The categories of this paper are: eess