A prominent example, which is the focus of this paper, is private machine learning, where a user often provides several points in the training data set.

Weexploit suchprototypes forboththe clustering and retrieval of unlabelled cardiac signals based on multiple patient attributes.

Empirical risk minimization (ERM) is a crucial framework that offers a general approach to handling a broad range of machine learning tasks.