Metric Learning

Metric Learning aims to learn a representation function that maps objects into an embedding space, where similar objects are closer to each other and dissimilar objects are farther apart. By optimizing various loss functions, such as contrastive loss and triplet loss, Metric Learning can effectively improve the accuracy of similarity measurement between objects, thereby playing a significant role in tasks like estimating arrival times.