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In addition, we consider here a subset of reliable edges that are not subject to failure.
Let only duplications and losses be considered, and let G be a binary gene tree with a predefined set of "reliable" edges.
Similarly, in [ 68] duplications, losses and transfers are accounted for to find a gene tree G′ such that it contains a predefined set of reliable edges (i.e., the induced clades) from G and minimizes the embedding cost of any mapping f of G′ into a given binary species tree S. A heuristic solving algorithm is proposed.
We conclude with an economical analysis which evaluates the incentive of using reliable edges in the network.
In this paper, we study the hop-constrained survivable network design problem with reliable edges.
We adapt for the two variants an extended formulation proposed in Botton, Fortz, Gouveia, Poss (2011) [1] for the case without reliable edges.
Our computational results indicate that these two variants appear to be more difficult to solve than the original problem (without reliable edges).
In situations where there are no reliable edges or structural content changes in the image pairs, SC fails to describe efficiently.
Nevertheless, the SFABD scheme achieves better contrast and produces more reliable edges, which is especially useful for segmentation and classification purposes necessary in medical image applications.
This selection of the most reliable edges is driven by both the criterion of sparseness and prior knowledge.
In order to identify the characterizing differences between two graphs, we searched for highly reliable edges which are present in the graph of one subpopulation but are absent in the graph of the other subpopulation.
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