I’m trying to find the answer to the question asked at
" Proper way to implement biases in Neural Networks "
Is the separation between the weights and biases due to: 1. readability of the implementation, 2. performance considerations, 3. flexibility/modularity, 4… others?
Please link to the relevant code if possible.
albanD
(Alban D)
December 1, 2019, 11:40pm
2
Hi,
I have the same opinion as most people on the link you sent:
It is easier to implement as you only do x*w +b. You don’t need to do concatenation of 1s to x.
The concatenation can be bad for performance.
You can easily get more flexibility in how to initialize or regularize them differently.