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omgitsjo t1_ivmay42 wrote

Reply to comment by No_Lingonberry2565 in [D] Simple Questions Thread by AutoModerator

You might be on to something. Not necessarily the inf norm, but maybe an asymmetric loss function. Guess zero when it's 0.1 and the penalty is much higher than guessing 0.1 when it is 0.

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No_Lingonberry2565 t1_ivmkyiw wrote

I suggested inf norm, because that will return a larger value, then when updating the weights through chain rule, it might lead to less sparse reduced states of your data

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