Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A scalable constructive algorithm for the optimization of neural network
  architectures   We propose a new scalable method to optimize the architecture of an
artificial neural network. The proposed algorithm, called Greedy Search for
Neural Network Architecture, aims to determine a neural network with minimal
number of layers that is at least as performant as neural networks of the same
structure identified by other hyperparameter search algorithms in terms of
accuracy and computational cost. Numerical results performed on benchmark
datasets show that, for these datasets, our method outperforms state-of-the-art
hyperparameter optimization algorithms in terms of attainable predictive
performance by the selected neural network architecture, and time-to-solution
for the hyperparameter optimization to complete.

22
The categories of this paper are: chao-dyn
20
The categories of this paper are: acc-phys
4
The categories of this paper are: cond-mat
30
The categories of this paper are: q-alg
25
The categories of this paper are: patt-sol
5
The categories of this paper are: gr-qc
0
The categories of this paper are: hep-ph
26
The categories of this paper are: bayes-an
31
The categories of this paper are: ao-sci
8
The categories of this paper are: hep-ex
28
The categories of this paper are: alg-geom
12
The categories of this paper are: nucl-th
15
The categories of this paper are: nucl-ex
10
The categories of this paper are: q-bio
14
The categories of this paper are: math-ph
37
The categories of this paper are: supr-con