[D] Has anyone figured out why Adam, RMSProp, And Adadelta don’t do well for training word embedding models, often worse than SGD?
It’s something I’ve heard here and there but never really got an explanation.
From online, I found this and this
Optimizers that build upon Adagrad aim to fix the vanishing learning rate problem, so why would they do worse?
Perhaps minimas are really unstable, and would benefit from the smaller learning rates. Could this issue then be alleviated by increasing the window of past gradients?