Your English writing platform
Discover LudwigSuggestions(5)
Exact(58)
Authors' response : Since we approximate the polynomial function with monotonic convex/concave constraints, the approximation is not over-parameterized.
The error of the approximation is controllable.
So in the end, the approximation is good enough.
Examples show that the approximation is of extremely high accuracy.
The approximation is derived from the Jensen inequality.
The approximation is done using least square method.
So the approximation is eventually of the first order level.
We find the sufficient condition when the approximation is relevant.
The approximation is progressively abandoned in later iterations.
where the constant in the approximation is independent of and.
where the approximation is accurate for sufficiently large m.
Write better and faster with AI suggestions while staying true to your unique style.
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