Solving quadratic programming problems via meta-controlled Boltzmann machine

The meta-controlled Boltzmann machine was proposed by J. Watada et. al. to solve the quadratic programming problem. It is shown that this model converges more efficiently than a conventional Boltzmann machine. In this paper, the inner behaviors of the model are evaluated in applying it to a quadratic programming problem, the portfolio selection problem.