Such constraint optimization problem could be solved by introducing Lagrange multiplier to incorporate the constraint: where λ x→y and λ y→x are the Lagrange parameters and the constraint is formulated as follows: Now the entire objective could be viewed as the standard supervised learning with an additional regularization term considering the duality between tasks.
the learning scheme is to learn the models by minimizing the weighted combination of an original loss term and a regularization term.