Wait, I'm confused...you're saying genetic approaches fell out of favor because they're basically just stochastic gradient descent? Most of modern DL relies heavily on SGD at various points during training.
My impression is that they fell out of favor precisely because don't actually use any gradients, and end up converging on good maxima slower than you could if you used the gradients from the net. Am I off base here?
My impression is that they fell out of favor precisely because don't actually use any gradients, and end up converging on good maxima slower than you could if you used the gradients from the net. Am I off base here?