Machine Learning, Artificial Intelligence, Regularization, Dropout Regularization, Overfitting.
a. L2 Regularization (strong): Consider the following linear regression problem with mean-squared loss. In L2 regularization, we modify the loss to include the weighted L2 norm of the weights (beta) being optimized. This prevents the weights from getting too large and hence avoiding them to