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Hybrid algorithms provide a compromise between the computational efficiency of a coarse-scale model and the representational accuracy of a fine-scale description.
3.4, given that our present training corpus is several times larger than the one used in [6] a direct comparison between the computational efficiency of these approaches is not possible.
The so-called hybrid smoother, combining advantages of the Laplacian and angle-based techniques is proposed to achieve the balance between the computational efficiency and quality of the mesh.
The difference between the computational efficiency trends of the algorithms under the same-domain and the across-domains settings is interesting.
Similar(56)
So, one can choose the appropriate m for a tradeoff between the better results and the computational efficiency [45].
There is, of course, a tradeoff between the accuracy, modularity, and the computational efficiency.
The main difference between the methods is discovered when the computational efficiency, measured in terms of error vs. run-time, is compared.
The computational efficiency and stability between RIA and PMA are compared.
They are designed considering the computational efficiency of the algorithms and a seamless interfacing between other procedures.
Computing some of the attractors on the synchronous model should improve the computational efficiency.
Hence the computational efficiency is improved considerably.
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