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6) You state that 'We have previously shown that our common-lines based programs do not suffer from the problems of over-fitting or model bias (Zhou et al., 2014)'.
We have previously shown that our common-lines-based programs do not suffer from the problems of over-fitting or model bias (Zhou et al., 2014).
And this is precisely what the scaremongering nonsense about gay people being out to get our children – a common line in the Ugandan debate – clearly demonstrates.
Conversely, common lines have positive effects when overtaking is possible.
The contribution of each common line to the estimated orientations is weighted according to a statistical model for common lines' detection errors.
In particular, any local optima in the common lines energy landscape do not affect the proposed algorithm.
The proposed algorithm finds the globally optimal assignment of orientations that simultaneously respects all common lines between all images.
The key property of the proposed algorithm is that it finds the global optimum for the orientations given the common lines.
With a case study we then illustrate that, if overtaking is not allowed, the presence of common lines worsens the service regularity along the corridor.
One of the most common lines first exchanged in any conversation with a stranger is, "What do you do?" Imagine having to struggle through the lengthy explanation.
Cracks that, in order to be filled, require the study and attention of those who, from afar, observe, analyze, and retrace common lines, without judging.
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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