Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Why and When Can Deep -- but Not Shallow -- Networks Avoid the Curse of
  Dimensionality: a Review   The paper characterizes classes of functions for which deep learning can be
exponentially better than shallow learning. Deep convolutional networks are a
special case of these conditions, though weight sharing is not the main reason
for their exponential advantage.

12
The categories of this paper are: nucl-th
29
The categories of this paper are: funct-an
10
The categories of this paper are: q-bio
25
The categories of this paper are: patt-sol
0
The categories of this paper are: hep-ph
2
The categories of this paper are: math
22
The categories of this paper are: chao-dyn
26
The categories of this paper are: bayes-an
14
The categories of this paper are: math-ph
35
The categories of this paper are: mtrl-th
4
The categories of this paper are: cond-mat
13
The categories of this paper are: quant-ph
6
The categories of this paper are: astro-ph
19
The categories of this paper are: eess
32
The categories of this paper are: atom-ph
18
The categories of this paper are: econ