Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Hyperparameter tuning of optical neural network classifiers for
  high-order gaussian beams   High-order Gaussian beams with multiple propagation modes have been studied
for free-space optical communications. Fast classification of beams using a
diffractive deep neural network, D2NN, has been proposed. D2NN optimization is
important because it has numerous hyperparameters, such as interlayer distances
and mode combinations. In this study, we classify Hermite-Gaussian beams, which
are high-order Gaussian beams, using a D2NN, and automatically tune one of its
hyperparameters known as the interlayer distance. We used the tree-structured
Parzen estimator, a hyperparameter auto-tuning algorithm, to search for the
best model. Results indicated that classification accuracy obtained by
auto-tuning hyperparameters was higher than that obtained by manually setting
interlayer distances at equal intervals. In addition, we confirmed that
accuracy by auto-tuning improves as the number of classification modes
increases.

25
The categories of this paper are: patt-sol
6
The categories of this paper are: astro-ph
34
The categories of this paper are: chem-ph
2
The categories of this paper are: math
16
The categories of this paper are: stat
14
The categories of this paper are: math-ph
0
The categories of this paper are: hep-ph
33
The categories of this paper are: plasm-ph
36
The categories of this paper are: cmp-lg
23
The categories of this paper are: solv-int
27
The categories of this paper are: comp-gas
18
The categories of this paper are: econ
4
The categories of this paper are: cond-mat
1
The categories of this paper are: cs
5
The categories of this paper are: gr-qc
21
The categories of this paper are: adap-org