4 ms·
You could probably derive some smart initialization for the first layer of a NN based on domain knowledge (color spaces, sobel filters, etc.). But since this is
by CodesInChaos 3y ago
You could probably derive some smart initialization for the first layer of a NN based on domain knowledge (color spaces, sobel filters, etc.). But since this is such a small part of what the NN has to learn, I expect this to result in a small improvement in training time and have no effect on final performance and accuracy, so it's unlikely to be worth the complexity of developing such a feature.
- whimsicalism 3y agoAbsolutely this. Seems like on HN people are still learning 'the bitter lesson'.
- CSSer 3y agoAmdahl’s law?
- nl 3y agoRick Sutton. http://www.incompleteideas.net/IncIdeas/BitterLesson.html http://www.incompleteideas.net/IncIdeas/BitterLesson.html
- CSSer 3y agoThank you!
- whimsicalism 3y agoSorry - should have included a cite. That said, Amdahl's law is also probably related in some degree - I would view YUV conversion as an unnecessary optimization.