A healthcare company is developing a machine learning model to analyze medical images and patient records to assist with diagnostics. The team has access to a large amount of unlabeled data and a smaller set of labeled data, and they are considering using semi-supervised learning to maximize the utility of both datasets. To make an informed decision on the approach, the data science team wants to understand which methods fall under semi-supervised learning. Which of the following are examples of semi-supervised learning? (Select two)