  Annealing machines specialized for combinatorial optimization problems have
been developed, and some companies offer services to use those machines. Such
specialized machines can only handle binary variables, and their input format
is the quadratic unconstrained binary optimization (QUBO) formulation.
Therefore, discretization is necessary to solve problems with continuous
variables. However, there is a severe constraint on the number of binary
variables with such machines. Although the simple binary expansion in the
previous research requires many binary variables, we need to reduce the number
of such variables in the QUBO formulation due to the constraint. We propose a
discretization method that involves using correlations of continuous variables.
We numerically show that the proposed method reduces the number of necessary
binary variables in the QUBO formulation without a significant loss in
prediction accuracy.
