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Discover LudwigThe term "fewer samples" is correct and usable in written English.
This term can be used in any context when comparing two or more groups (not necessarily numbers) of something. For example, "In this experiment, we collected fewer samples than in our last trial."
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This resulted in greater sampling from bins with fewer samples available.
But in practice, it means fewer samples per track, and it can make complex assemblages prohibitively expensive.
Compared with the traditional model, TFRWν-SVM method requires fewer samples and has better forecasting precision.
The effect of using representative calibration sets with fewer samples was explored and discussed.
Can I use ideas related to this to try to recover from much fewer samples than that.
Experimental results show our method achieves higher segmentation accuracy than FSL methods with fewer samples and reduced training effort.
Quantitatively, the former requires several thousands fewer samples to converge to the same steady-state solution achieved by the latter.
This key observation has led to the design of sensing systems that can directly capture the information using far fewer samples typically acquired via random projections.
A potentially better approach would be to render them with fewer samples and then do some image processing on the noisy ones.
I rendered images more quickly by breaking down the lights one at a time and by rendering in lower resolution with fewer samples per pixel, as recommended.
As recommended, I used a lower resolution and fewer samples per pixel while experimenting than I did in rendering my final submissions.
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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