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If we would have a closed-form expression for such proximity operator or if we could approximate it efficiently (with the approximation errors decreasing at appropriate rates [27]), then we could efficiently solve (7).
With respect to the effects of training mode, we observed a significant advantage of mode Rhyme&Melody as of Session 3. From the start, this effect interacted with the training method, with the number of gender errors decreasing most clearly in the blocked Rhyme&Melody group (see Fig. 3).
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For staircase signals, both rise times and mean steady-state errors decreased.
Omission errors as proportion of total errors decreased over the course of the study for both treatment groups.
The errors decrease the accuracy of the EEW system.
The errors decreased as the number of modeled sequences increased.
As the target errors decreased from 0.10 to 0.005, the mean squared errors also decreased from 0.086 to 0.003.
Burnout, in turn, leads to possible errors, decreased productivity, early retirement of critically skilled workers and in some cases, the tragedy of suicide.
It may be expected that the errors decrease if we use data closer to the source.
It could be seen that the errors decreased sharply at the beginning.
In the second pass, the total number of errors decreased by 1.65% relatively.
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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