Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Fitting the Search Space of Weight-sharing NAS with Graph Convolutional
  Networks   Neural architecture search has attracted wide attentions in both academia and
industry. To accelerate it, researchers proposed weight-sharing methods which
first train a super-network to reuse computation among different operators,
from which exponentially many sub-networks can be sampled and efficiently
evaluated. These methods enjoy great advantages in terms of computational
costs, but the sampled sub-networks are not guaranteed to be estimated
precisely unless an individual training process is taken. This paper owes such
inaccuracy to the inevitable mismatch between assembled network layers, so that
there is a random error term added to each estimation. We alleviate this issue
by training a graph convolutional network to fit the performance of sampled
sub-networks so that the impact of random errors becomes minimal. With this
strategy, we achieve a higher rank correlation coefficient in the selected set
of candidates, which consequently leads to better performance of the final
architecture. In addition, our approach also enjoys the flexibility of being
used under different hardware constraints, since the graph convolutional
network has provided an efficient lookup table of the performance of
architectures in the entire search space.

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The categories of this paper are: supr-con
3
The categories of this paper are: physics
12
The categories of this paper are: nucl-th
19
The categories of this paper are: eess
17
The categories of this paper are: q-fin
10
The categories of this paper are: q-bio
32
The categories of this paper are: atom-ph
15
The categories of this paper are: nucl-ex
29
The categories of this paper are: funct-an
6
The categories of this paper are: astro-ph
24
The categories of this paper are: dg-ga
9
The categories of this paper are: nlin
11
The categories of this paper are: hep-lat
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The categories of this paper are: cmp-lg
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The categories of this paper are: hep-ex
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The categories of this paper are: plasm-ph