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In particular, the proposed metric provides wider working range and more precise prediction consistency under all tested deformation conditions although it is slightly expensive in terms of computation than other metrics.
However, this aggregation scheme is very expensive in terms of computation.
Firstly, a cost-based enumeration may be very expensive in terms of computation resources.
The proposed solutions using this approach are very effective for privacy protection but very expensive in terms of computation and communication.
This approach yields a suboptimal solution, but it is more tractable and less expensive in terms of computation power and data storage.
Unfortunately, the cryptographic algorithms for this purpose are expensive in terms of computation and communication, which mostly require smart meters to be involved in the computation [15 18].
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Sobel operator is also less expensive in terms of computations because it computes absolute gradient magnitude, which is an integer value.
Both approaches can be extremely expensive in terms of computational time.
Selecting too large a value of the independent variable is expensive in terms of computer time.
However, Gabor-based methods and DERF are quite expensive in terms of computational cost.
However, a dilemma we have to face is that, on the one hand, the labeled patterns play a pivotal role for the learning algorithms; but on the other hand, labeling patterns is often expensive in terms of the computation time or cost, particularly for the large-scale streaming data, which is intractable.
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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