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  2. Cut (graph theory) - Wikipedia

    en.wikipedia.org/wiki/Cut_(graph_theory)

    If s and t are specified vertices of the graph G, then an s – t cut is a cut in which s belongs to the set S and t belongs to the set T. In an unweighted undirected graph, the size or weight of a cut is the number of edges crossing the cut. In a weighted graph, the value or weight is defined by the sum of the weights of the edges crossing the ...

  3. Blossom algorithm - Wikipedia

    en.wikipedia.org/wiki/Blossom_algorithm

    The matching problem can be generalized by assigning weights to edges in G and asking for a set M that produces a matching of maximum (minimum) total weight: this is the maximum weight matching problem. This problem can be solved by a combinatorial algorithm that uses the unweighted Edmonds's algorithm as a subroutine. [6]

  4. Deming regression - Wikipedia

    en.wikipedia.org/wiki/Deming_regression

    In statistics, Deming regression, named after W. Edwards Deming, is an errors-in-variables model that tries to find the line of best fit for a two-dimensional data set. It differs from the simple linear regression in that it accounts for errors in observations on both the x- and the y- axis.

  5. Handshaking lemma - Wikipedia

    en.wikipedia.org/wiki/Handshaking_lemma

    In any graph, the degree ⁡ of a vertex is defined as the number of edges that have as an endpoint. For graphs that are allowed to contain loops connecting a vertex to itself, a loop should be counted as contributing two units to the degree of its endpoint for the purposes of the handshaking lemma. [2]

  6. Incidence matrix - Wikipedia

    en.wikipedia.org/wiki/Incidence_matrix

    It is the incidence matrix of any bidirected graph that orients the given signed graph. The column of a positive edge has a 1 in the row corresponding to one endpoint and a −1 in the row corresponding to the other endpoint, just like an edge in an ordinary (unsigned) graph. The column of a negative edge has either a 1 or a −1 in both rows.

  7. Logic of graphs - Wikipedia

    en.wikipedia.org/wiki/Logic_of_graphs

    If a first-order graph property has probability tending to one on random graphs, then it is possible to list all the -vertex graphs that model the property, with polynomial delay (as a function of ) per graph. [4] A similar analysis can be performed for non-uniform random graphs, where the probability of including an edge is a function of the ...

  8. Boundary (graph theory) - Wikipedia

    en.wikipedia.org/wiki/Boundary_(graph_theory)

    The edge boundary is the set of edges with one endpoint in the inner boundary and one endpoint in the outer boundary. [1] These boundaries and their sizes are particularly relevant for isoperimetric problems in graphs, separator theorems, minimum cuts, expander graphs, and percolation theory.

  9. Closed graph theorem (functional analysis) - Wikipedia

    en.wikipedia.org/wiki/Closed_graph_theorem...

    The Borel graph theorem, proved by L. Schwartz, shows that the closed graph theorem is valid for linear maps defined on and valued in most spaces encountered in analysis. [10] Recall that a topological space is called a Polish space if it is a separable complete metrizable space and that a Souslin space is the continuous image of a Polish space.