Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Discretization-Aware Architecture Search   The search cost of neural architecture search (NAS) has been largely reduced
by weight-sharing methods. These methods optimize a super-network with all
possible edges and operations, and determine the optimal sub-network by
discretization, \textit{i.e.}, pruning off weak candidates. The discretization
process, performed on either operations or edges, incurs significant inaccuracy
and thus the quality of the final architecture is not guaranteed. This paper
presents discretization-aware architecture search (DA\textsuperscript{2}S),
with the core idea being adding a loss term to push the super-network towards
the configuration of desired topology, so that the accuracy loss brought by
discretization is largely alleviated. Experiments on standard image
classification benchmarks demonstrate the superiority of our approach, in
particular, under imbalanced target network configurations that were not
studied before.

28
The categories of this paper are: alg-geom
33
The categories of this paper are: plasm-ph
22
The categories of this paper are: chao-dyn
30
The categories of this paper are: q-alg
6
The categories of this paper are: astro-ph
4
The categories of this paper are: cond-mat
11
The categories of this paper are: hep-lat
35
The categories of this paper are: mtrl-th
16
The categories of this paper are: stat
14
The categories of this paper are: math-ph
10
The categories of this paper are: q-bio
26
The categories of this paper are: bayes-an
29
The categories of this paper are: funct-an
8
The categories of this paper are: hep-ex
27
The categories of this paper are: comp-gas
15
The categories of this paper are: nucl-ex