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I'm new here so this may be a very easy question. Is there any way to restrict the weights and bias in the whole training process, like being nonnegative all the time? I just find in the doc that I can give a constraint on initial weights and bias, while I wonder if it is feasible in the whole process.
Thanks!
The text was updated successfully, but these errors were encountered:
I am not very up to date with the literature here, but typically, these constraints can be applied using a reparameterization. For example, you can have unconstrained weights but apply an exp transform before feeding it into your model.
Hi,
I'm new here so this may be a very easy question. Is there any way to restrict the weights and bias in the whole training process, like being nonnegative all the time? I just find in the doc that I can give a constraint on initial weights and bias, while I wonder if it is feasible in the whole process.
Thanks!
The text was updated successfully, but these errors were encountered: