Figure 1
From: Quantum adversarial metric learning model based on triplet loss function
Sample space change in metric learning process. Before metric learning, the distances between negative sample pairs are smaller, and samples from different classes are difficult to separate by linear functions. After metric learning, the distances between negative sample pairs become larger, and a large margin separates samples from different classes. Linear functions can easily separate positive and negative samples