Which paper/blog post/book specifically documents the most recent research? E.g. just yesterday I figured out (after surfing the internet for a long time) that the diminishing gradient problem have essentially been solved by ReLUs, so auto-encoders are no longer necessary and we can train a whole deep network at once. Another is e.g. batch regularization. Probably not news for a researcher, but where could I learn these updates?