Deep-Autoencoders-For-Collaborative-Filtering
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l2 regularization of weights only
Modified l2_loss
term so that it does not count biases, only weights. Typically we do not want to regularize biases as they are:
- additive, not multiplicative, and so are far less likely to cause numeric issues if they get too large, and
- not necessarily limited by real-world constraints to be near zero.
Basically our data can have biases that are far from zero, so we shouldn't try to keep them close to zero.