What is the goal of unsupervised machine learning?
The paper explores unsupervised machine learning by proposing four distinct, often orthogonal, goals: estimating data distributions, generating new data points, extracting features for downstream tasks, and understanding data structure. It discusses methods for each goal and highlights that these goals are not mutually exclusive but rather independent objectives.