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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
by tomp 10y ago
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?
- mrdrozdov 10y agoThe only way to really stay caught up is to read the papers that are being released (NIPS, ICML, ICLR, CPVR, etc). If you use a course or guide, then you're behind by definition. If you're okay with being a little behind, then the Deep Learning courses for NLP or Computer Vision are both excellent. NYU also has similar courses. You can also try following some major Deep Learning people on Facebook/Twitter as they post about the new stuff daily. People to follow: Lecun, Lawrence, Bengio, Cho, Karpathy, just to name a few. Interested to hear others ideas on how to stay up to date.