Adversarial learning is a technique used in neural structure learning to improve the robustness and generalization of neural network models. In this approach, adversarial neighbors are connected to the original samples to construct the structure in neural structure learning. These adversarial neighbors are generated by perturbing the original samples in a way that maximizes the