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TEEN is known as one of the most efficient algorithms in terms of energy efficiency (Pantazis et al. 2013; Liu 2012).

The most efficient algorithms for PSAT apply linear programming techniques to this set of constraints.

Reactive transport is a highly non-linear problem requiring the most efficient algorithms to rapidly reach an accurate solution.

Combining inference rules with linear programming techniques leads to the currently most efficient algorithms, as showed in ref. [18].

CET classifies as feasible those functions whose most efficient algorithms have time complexity \(c \cdot n^k\) for arbitrarily large scalar factors \(c\) and exponents \ k\).

Our comprehensive experimental study on synthetic and real the proposed approaches are the most efficient algorithms for RkNN and its variants.

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We compare our algorithm with the ESHN algorithm, which was reported to be the most efficient algorithm for dynamic multicast traffic protection in terms of resource utilization efficiency and blocking probability.

The most efficient algorithm for addition, for instance, involves stacking numbers to be added with their place values aligned, successively adding single digits beginning with the ones place column, and "carrying" any extra place values leftward.

From above two examples, we can conclude that our algorithm is the most efficient algorithm for categorical data clustering.

SLICE [2] is the most efficient algorithm before our work for RkNN, which is integrated in our query processing algorithm in this paper.

Recently, Tang et al. [Inform. Process. Lett. 77 (2001) 17 22] proposed an interesting O △1⋅n2) algorithm for this problem, which has been considered its most efficient algorithm since.

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