How does MLC verify results without running multiple tasks per work unit (redundancy)?

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W8n4Singularity
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Message 1136 - Posted: 7 Apr 2021, 2:46:38 UTC
Last modified: 7 Apr 2021, 2:47:10 UTC

Asking just out of curiosity.

Some older tasks did have other canonical results such as this one: https://www.mlcathome.org/mlcathome/workunit.php?wuid=1120016
Newer tasks are validated without redundancy: https://www.mlcathome.org/mlcathome/workunit.php?wuid=2602952

Thanks!
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An0ma1y
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Message 1138 - Posted: 7 Apr 2021, 19:40:13 UTC

hmm, i hadn't noticed this, but this is a very good question, i would like to know this as well.
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bozz4science

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Message 1139 - Posted: 8 Apr 2021, 11:53:31 UTC

Isn't each network learning task a stochastic process, in the sense that no 2 tasks will ever (very unlikely) produce the same result?
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Message 1141 - Posted: 8 Apr 2021, 20:09:45 UTC - in response to Message 1139.  
Last modified: 8 Apr 2021, 20:10:12 UTC

Very interesting. If that is the case, does that also mean that MLC would need to process far more results to reach statistical significance versus a project that uses redundancy and can prove that the calculated results are valid?
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pianoman [MLC@Home Admin]
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Message 1150 - Posted: 16 Apr 2021, 21:11:08 UTC

Each network is compared against a test dataset that is held back from being sent to you users. If the network performs well on that test set (and is a valid network, and is not identical to a previously submitted result) then it is considered valid.
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Message 1151 - Posted: 16 Apr 2021, 21:14:34 UTC

I'm working on adding a few more criteria that I'll keep vague to stop potential cheating, but in general that's why we don't do multiple results per WU, because they're stochastic and won't be identical at all. In fact, this stochastic nature is what we're trying to capture so it helps.
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Message boards : Cafe : How does MLC verify results without running multiple tasks per work unit (redundancy)?

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