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Experimental results on a classification task using two action benchmark datasets show that our model is competitive with state-of-the-art methods for batch learning also when a significant number of sample labels are missing or corrupted during training sessions.
While such a homophily-based method is very efficient at predicting a small portion of missing labels in the full social graph, they are inefficient for our use case focused on low and middle income countries where the vast majority of the labels are missing and collecting training data through surveys is costly.
And that's the major problem the major labels are missing.
During tuning, the user may discover that the distant supervision labels are missing an entire class of relations and thus incorrectly labeling candidates.
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The wall labels were missing.
In the originally published article, two panel labels were missing in the legend for Extended Data Fig. 1.
In the version of this article initially published, '+' and '–' labels were missing from the graph keys at the bottom of Fig. 8d.
A quality control technician said he tried to stop the production line when he noticed that some labels were missing, but was overruled by management.
And on this he would not budge, deducting points when this label was missing.
In the even that a cantaloupe label is missing, the CDC has a simple piece of advice: "When in doubt, throw it out".
In the even that a cantaloupe label is missing, the CDC has a simple piece of advice: "When in doubt, throw it out". Photo by Flickr user mrsdkrebs.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com