Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Landscape analysis for shallow neural networks: complete classification
  of critical points for affine target functions   In this paper, we analyze the landscape of the true loss of one-hidden-layer
networks with ReLU, leaky ReLU, as well as with quadratic activation. In all
three cases, we provide a complete classification of the critical points in the
case where the target function is affine. In particular, we show that there
exist no local maxima and clarify the structure of saddle points. Moreover, we
prove that non-global local minima can only be caused by `dead' ReLU neurons.
In particular, they do not appear in the case of leaky ReLU or quadratic
activation. Our approach is of a combinatorial nature and builds on a careful
analysis of the different types of hidden neurons that can occur.

18
The categories of this paper are: econ
28
The categories of this paper are: alg-geom
33
The categories of this paper are: plasm-ph
34
The categories of this paper are: chem-ph
31
The categories of this paper are: ao-sci
10
The categories of this paper are: q-bio
19
The categories of this paper are: eess
23
The categories of this paper are: solv-int
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
22
The categories of this paper are: chao-dyn
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
9
The categories of this paper are: nlin
17
The categories of this paper are: q-fin