An iterative optimization method that updates parameters by moving them opposite to the gradient of an objective function, scaled by a step size, to reduce the function value.
An iterative optimization method that updates variables by moving in the direction opposite to the gradient of an objective function to reduce its value, typically using step-size (learning rate) control.