Suggestions(3)
Exact(19)
The dimension problem.
We point out the critical dimension problem of CENI framework.
Discrete graphs allow for a nice solution to the dimension problem, that was mentioned in section 2.5.
Another related problem is the higher dimension problem with exponential nonlinearity.
By addressing the critical dimension problem, we propose the third implementation of the CENI framework: Projection-based CENI.
First, we embed the solution of ((mathcal {P}_{0} )), into the larger dimension problem ((mathcal {P}_{A})).
Similar(41)
In their paper, only low dimension problems (two variables) are tested.
However, even though the global convergence of PS has been proved, it does not perform well on more complex and higher dimension problems nowadays.
The classification capability of DS-ECA is promising since it can describe very complicated decision rule in high dimension problems with less complexity.
However, classifiers dealing with complicated high dimension problems with non-conforming patterns with high accuracy are rare, especially for bit-level features.
In addition, it can offer a good classification accuracy for low dimension problems which may be the case in our study, because the number of features was efficiently reduced in previous steps [ 18].
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