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Our edge-covering solution, EdgeCoveringTwoRobots (Algorithm 4), is an adaptation of the GraphConvergenceTwoRobots algorithm in the previous section.
It employs an adaptation of the Nemhauser Ullman algorithm for the 0 1 knapsack problem (4).
The first approach Matsen et al. (2013) considered for minimizing ADCL is an adaptation of the PAM algorithm.
This is an adaptation of the adaptive GMM algorithm first described by Stauffer et al. [21].
This algorithm is an adaptation of the framework of [ 10] (see also [ 11]).
The remaining part of the allele-specific PCF algorithm is then essentially an adaptation of the multi-sample PCF algorithm applied to two samples.
This algorithm starts with an adaptation of the optical flow and includes a thresholding operation.
This requires the adaptation of the algorithm to the negative binomial distribution with which we model the data.
This requires an appropriate adaptation of the proposed algorithm to the coding of the excitation (residual signal).
The algorithm is an adaptation of Williams' matrix-vector multiplication algorithm over a finite semiring [ 13], with some notions similar to those in Frid and Gusfield's RNA folding algorithm [ 14].
For the calculation of the maximum flow we used an adaptation of Cherkassky and Goldberg's maximum flow algorithm [8].
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