Quantum annealing is a generic solver of combinatorial optimization problem and is implemented by a hardware known as the D-Wave quantum annealer.
On the other hand, the neural network, which is a big success in developing the artificial intelligence and data science, is also attained via solving optimization problem.
In this talk, by taking the quantum annealer as an optimizer, we introduce several directions of its application.
One of the main topic would be an application of the quantum annealer to the deep neural network although the standard one only deal with the binary variables.
In addition, we will report a new type of the applications with machine learning.
Back to Workshop IV: Using Physical Insights for Machine Learning