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notdelet t1_j9g627c wrote

> Assuming Gaussianity and then using maximum likelihood gives yields an L2 error minimization problem.

Incorrect, only true if you fix the scale parameter. I normally wouldn't nitpick like this but your unnecessary usage of bold made me.

> (if you interpret training as maximum likelihood estimation)

> a squared loss does not "hide a Gaussian assumption".

It does... if you interpret training as (conditional) MLE. Give me a non-Gaussian distribution with an MLE estimator that yields MSE loss. Also, residuals are explicitly not orthogonal projections whenever the variables are dependent.

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notdelet t1_j9gija3 wrote

In the future know that blocking someone after replying to them prevents them from responding to your reply. This means you are giving the false impression I am not responding to you (but can) to those who are not one of us.

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