What is the main advantage of mini$-$batch gradient descent over full batch gradient descent?

Group of answer choices

It is more computationally efficient, as it only uses a subset of the training data at each iteration

It is better suited for online learning

It has a higher chance of reaching the global minimum of the cost function

It is more robust to noise in the training data