In the context of Empirical Risk Minimization, the process of selecting parameters that minimize the average loss is often referred to as __________.

Empirical Risk Minimization means choosing the model that makes the average loss on the data as small as possible. Other options are incorrect because Maximum Likelihood Estimation is about finding parameters that make the observed data most likely, not about reducing average loss; Bayesian Optimization is a technique that uses a probabilistic model to search for a minimum of a function, but it does not directly minimize the average loss of a model on data.