Early Stopping stops training when validation scores start getting worse.
Early Stopping is pulling cookies out at golden brown. Wait for "extra sure," and you make tiny hockey pucks.
In neural network training, it watches validation scores and stops when they slip. This saves compute and helps stop overfitting.
Regularization
Early Stopping works as Regularization by stopping early and reducing overfitting.
Cross-Validation
Cross-Validation gives validation scores for deciding when to stop training.
Gradient Descent
Early Stopping usually happens during Gradient Descent training.