Machine Learning, Gradient Descent, Optimization, Deep Learning, Artificial Intelligence.
Adam : 0 at [-8.89, -61.51] SGD : 0 at [-8.89, -61.51] RMSProp : 0 at [-8.89, -61.51] AdaDelta : 0 at [-8.89, -61.51] AdaGrad : 0 at [-8.89, -61.51] AdamW : 0 at [-8.05, -55.66] Note that for Eason function the gradient is almost zero, except near the origin and takes the value 0. Hence none of the