4 ms·
Sadly, no. This OP's writeup is just about the simplest exposition that doesn't miss the point, and it misses the major transition when you go to layers with no
by madhadron 7y ago
Sadly, no. This OP's writeup is just about the simplest exposition that doesn't miss the point, and it misses the major transition when you go to layers with nonlinearities between them.
There is no royal road to mathematics.
- cr0sh 7y ago> This OP's writeup is just about the simplest exposition that doesn't miss the point, and it misses the major transition when you go to layers with nonlinearities between them. Well - the activation function appears to be linear, and thus close to RELU - and so (maybe?) there wouldn't be any issue with the so-called "vanishing gradients" problem? But I am just a hobbyist who dabbles in this topic, so my opinion doesn't carry much weight...
- madhadron 7y agoThere is no activation function. It's linear regression.
- derangedHorse 7y agoTo be fair, there’s also no layers in linear regression
- derangedHorse 7y agoI think there might be a fun idea in that. I wonder what kind of learning materials we could generate by holding competitions on who could explain a topic the simplest