Why does using Gradient descent over Stochatic gradient descent improve performance?
SGD has a regularization effect and finds the solution faster. GD on the other hand takes a look at whole data and finds the next best step.
SGD may be come to optimal global minima but GD can. But GD is not practical with large data.