Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Convergence rates for the stochastic gradient descent method for
  non-convex objective functions   We prove the local convergence to minima and estimates on the rate of
convergence for the stochastic gradient descent method in the case of not
necessarily globally convex nor contracting objective functions. In particular,
the results are applicable to simple objective functions arising in machine
learning.

12
The categories of this paper are: nucl-th
17
The categories of this paper are: q-fin
8
The categories of this paper are: hep-ex
20
The categories of this paper are: acc-phys
10
The categories of this paper are: q-bio
15
The categories of this paper are: nucl-ex
25
The categories of this paper are: patt-sol
26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg
7
The categories of this paper are: hep-th
18
The categories of this paper are: econ
31
The categories of this paper are: ao-sci
11
The categories of this paper are: hep-lat
34
The categories of this paper are: chem-ph
36
The categories of this paper are: cmp-lg
6
The categories of this paper are: astro-ph