In adversarial training, we seek parameters (saddle point) such that which involves a maximization with respect to Ψ and a minimization with respect to {Λ, Φ, Ω}.
the updates of the shared parameters Λ = {U, V } for the discriminator work adversarially to the rest of the network, and vice versa.