In particular, this algorithmic approach provides insight into efficiency criteria for identifying conditions under which increasing block production has a negative impact on the stability of a blockchain. The
In addition, optimization is the most time-consuming step during inverse analysis, but we apply algorithmic differentiation to increase the computational efficiency52. Algorithmic differentiation can compute gradients with a low computational cost for complicated computer programs by applying the chain rule ...
There are, of course problems where either the computational aspects are unchallenging so that only effectiveness requires the analyst's attention; or where the problem is in principle well-defined but computationally complex, so that efficiency concerns dominate. Contexts do arise in which structuring...
In this approach, each possible combination of GA operators was considered as a decision making unit (DMU), and DEA was adopted to evaluate and compare the algorithmic efficiency of the distinct GA combinations under consideration. In addition, the cross-efficiency (CE) method (e.g., Doyle &...
Before assessing the clustering performances of FLAME, we preliminarily estimated its computational efficiency by analyzing its time complexity [seeAdditional file 2]. As a theoretic time complexity estimation of the membership approximation procedure is very difficult, we performed an empirical study of ...
An algorithmic mathematical tool called the KF is used to estimate variables over time intervals by taking into account noise and observed measures. It provides precise estimates of the state of a system by computing joint probability distributions across variables for every timeframe. It is appropria...
If not already done, algorithmic tuning techniques like parallelization and vectorization can help improve the performance of code regions that fall into the retiring category. Conclusion The Top-Down Method and its availability in VTune Profiler represent a new direction for performance tu...
AI in computer vision can be affected by algorithmic bias and discrimination in various applications such as face recognition and security. This leads to unfair market outcomes and a slow market adoption process. Also, when making decisions based on sensitive information, the secrets surrounding AI ...
We first analyze the effectiveness of the first measure, grouping efficiency. A worst case bound is then derived for the minimum spanning tree algorithm with respect to this measure. We then show a newly proposed measure, grouping efficacy, is not suitable from an algorithmic point of view. A...
of a 2.6 GHz Intel Xeon Platinum 8358 CPU. For neural network methods, we additionally used an A100 GPU to accelerate calculations and monitored the runtime over a total of 50 epochs, a commonly accepted minimum number of epochs required for algorithmic convergence. Our findings, illustrated...