Instead of making a training/validation split, we could also use cross-validation to search for good values for our hyperparameters. What is the advantage of this approach? It is more time-efficient. It is a faster way to choose hyperparameters It is more data-efficient. Each example gets to be used as training data. It removes the need for a separate test set. It ensures that the optimization algorithm converges faster