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Dechter conjectured this computation problem to be NP-hard.
Then considering the specialties of network distance computation problem, an efficient way supported by flow extension simulation is proposed.
The other approaches like Multiple Kernel Learning MKLL) and deep core vector machines solve the fixed kernel computation problem and scalability aspects of MKMs respectively.
This design is quite innovative as it provides a viable solution to the fitness computation problem, which depends heavily on the problem-specific knowledge.
To solve the surface integral equation, especially when the rough surface is very large in terms of the wavelength, we treat the large-scale matrix computation problem which is generated by the fast multipole algorithm using the RCGM.
For a large scale computation problem such as the wave interaction with a very large structure or a large number of bodies, the BEMs with the FMM and pFFT accelerations are discussed, respectively, including the principles of the FMM and the pFFT, and their implementations in various integral equations with different Green functions.
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Parallel computing divides large computation problems into smaller ones, which are then solved concurrently.
Theory and algorithm development for large matrix computation problems arising in computational science and engineering.
It analyses borrow pit computation problems related to soil phases and provides an introduction to seismology.
Design sensitivity analysis is mainly applicable to optimization and force computation problems.
Graph computation problems that exhibit irregular memory access patterns are known to show poor performance on multiprocessor architectures.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com