weakly supervised learning
machine learning approach where noisy, limited, or imprecise sources are used to provide supervision signal for labeling large amounts of training data in a supervised learning setting
semi-supervised learning
class of machine learning techniques combining a small amount of labeled data with a large amount of unlabeled data during training
self-supervised learning
class of machine learning techniques in which a task is solved based on pseudo-labels which help initialize weights the weight, then the actual task is performed with supervised or unsupervised learning