Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Teaching a neural network with non-tunable exciton-polariton nodes   In contrast to software simulations of neural networks, hardware or
neuromorphic implementations have often limited or no tunability. While such
networks promise great improvements in terms of speed and energy efficiency,
their performance is limited by the difficulty to apply efficient teaching. We
propose a system of non-tunable exciton-polariton nodes and an efficient
teaching method that relies on the precise measurement of the nonlinear node
response and the subsequent use of the backpropagation algorithm. We
demonstrate experimentally that the classification accuracy in the MNIST
handwritten digit benchmark is greatly improved compared to the case where
backpropagation is not used.

24
The categories of this paper are: dg-ga
16
The categories of this paper are: stat
32
The categories of this paper are: atom-ph
3
The categories of this paper are: physics
22
The categories of this paper are: chao-dyn
14
The categories of this paper are: math-ph
19
The categories of this paper are: eess
12
The categories of this paper are: nucl-th
37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
34
The categories of this paper are: chem-ph
28
The categories of this paper are: alg-geom
33
The categories of this paper are: plasm-ph
31
The categories of this paper are: ao-sci