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Additionally, there are also metrics for which computations performed in the linear and logarithm domains perform better than in the PU and PQ space.
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The following illustrates an example of a satisfiable constraint for which computation of satisfiability involves computing satisfiability of constraints (pi ^{prime }) that unify with a constraint head (pi _0) such that (eta (pi ^{prime })) is greater than the upper bound associated to (pi _0).
Note that when the kernel method is adopted, direct use of MKDA, for which computation depends only on the inner products in the feature space, becomes difficult due to the large amount of training data.
To create a metric of long-term exposure, we took the average of the 365 daily estimate at the participant's residential address prior to the date of the first cognitive assessment completed on or after 1 January 1996, the first date for which computation of a prior 1-year average was possible.
Because much of the previous research has focused on the sharing mechanism of GPUs among VMs, they cannot achieve enough performance for biological applications of which computation throughput is more crucial rather than sharing.
The Curry-Howard correspondence has made intuitionistic natural deduction part of the computer science curriculum: it gives a computational semantics for intuitionistic logic in which computations, and the executions of programs more generally, are effected through normalization.
Of primary concern in future design iterations is the voltage droop, which computations underestimated for the current design.
This has favorable implications for both stability analysis, where small numerical errors in the energy may significantly affect the computation of marginal points, and transport applications, for which equilibrium computations on coarse meshes are desirable.
This includes the use of specialized software to facilitate some of the computationally heavy techniques for which hand computations are not feasible.
We first derive the joint probability density of the data, for which the computation of the covariance matrix is critical.
Moreover, we derive the conditions for which the computation can be implemented by time independent as well as by adiabatically varying Hamiltonians.
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