Computer scienceData scienceMachine learningIntroduction to deep learningOptimizers

Gradient descent with momentum

Advantages and limitations

Report a typo

Select the correct statements about the advantages and limitations of GD with momentum.

Select one or more options from the list

Momentum GD makes the optimization process less sensitive to the choice of learning rate

Momentum GD accelerates convergence

Momentum GD does not guarantee escape from narrow local minima

Momentum GD prevents overfitting

___

Create a free account to access the full topic