Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: LENS: Layer Distribution Enabled Neural Architecture Search in
  Edge-Cloud Hierarchies   Edge-Cloud hierarchical systems employing intelligence through Deep Neural
Networks (DNNs) endure the dilemma of workload distribution within them.
Previous solutions proposed to distribute workloads at runtime according to the
state of the surroundings, like the wireless conditions. However, such
conditions are usually overlooked at design time. This paper addresses this
issue for DNN architectural design by presenting a novel methodology, LENS,
which administers multi-objective Neural Architecture Search (NAS) for
two-tiered systems, where the performance objectives are refashioned to
consider the wireless communication parameters. From our experimental search
space, we demonstrate that LENS improves upon the traditional solution's Pareto
set by 76.47% and 75% with respect to the energy and latency metrics,
respectively.

5
The categories of this paper are: gr-qc
10
The categories of this paper are: q-bio
24
The categories of this paper are: dg-ga
2
The categories of this paper are: math
31
The categories of this paper are: ao-sci
16
The categories of this paper are: stat
15
The categories of this paper are: nucl-ex
37
The categories of this paper are: supr-con
6
The categories of this paper are: astro-ph
35
The categories of this paper are: mtrl-th
9
The categories of this paper are: nlin
12
The categories of this paper are: nucl-th
4
The categories of this paper are: cond-mat
21
The categories of this paper are: adap-org
33
The categories of this paper are: plasm-ph
29
The categories of this paper are: funct-an