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markburns | 1 year ago

That seems an uncharitable view of the reply.

The search space is huge, we sometimes find needles in haystacks by accident, isn’t it exciting that we have tools now that can systematically check every piece of hay?

discuss

order

richrichie|1 year ago

ML search is more about ‘averages’ based on samples.

Innovations like these are more about ‘shocks’ that surface fitting cannot capture.

Note universal approximation theorem applies only to smooth surfaces.

tomrod|1 year ago

Not always. Quantile regression exists. And you can develop "no match" categories.

radarsat1|1 year ago

But the better the mean surface is fitted (in a generizable way), the easier it is to spot outliers.