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  2. Kullback–Leibler divergence - Wikipedia

    en.wikipedia.org/wiki/Kullback–Leibler_divergence

    A simple interpretation of the KL divergence of P from Q is the expected excess surprise from using Q as a model instead of P when the actual distribution is P. While it is a measure of how different two distributions are, and in some sense is thus a "distance", it is not actually a metric, which is the most familiar and formal type of distance.

  3. Koutecký–Levich equation - Wikipedia

    en.wikipedia.org/wiki/Koutecký–Levich_equation

    B L is the Levich Constant. ω is the angular rotation rate of the electrode (rad/s) From an experimental data set where the current is measured at different rotation rates, it is possible to extract the kinetic current from a so-called Koutecký–Levich plot.

  4. Kosambi–Karhunen–Loève theorem - Wikipedia

    en.wikipedia.org/wiki/Kosambi–Karhunen–Loève...

    The covariance function K X satisfies the definition of a Mercer kernel. By Mercer's theorem, there consequently exists a set λ k, e k (t) of eigenvalues and eigenfunctions of T K X forming an orthonormal basis of L 2 ([a,b]), and K X can be expressed as

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  6. Cross-entropy - Wikipedia

    en.wikipedia.org/wiki/Cross-entropy

    In information theory, the cross-entropy between two probability distributions and , over the same underlying set of events, measures the average number of bits needed to identify an event drawn from the set when the coding scheme used for the set is optimized for an estimated probability distribution , rather than the true distribution .

  7. Kernighan–Lin algorithm - Wikipedia

    en.wikipedia.org/wiki/Kernighan–Lin_algorithm

    The input to the algorithm is an undirected graph G = (V, E) with vertex set V, edge set E, and (optionally) numerical weights on the edges in E.The goal of the algorithm is to partition V into two disjoint subsets A and B of equal (or nearly equal) size, in a way that minimizes the sum T of the weights of the subset of edges that cross from A to B.

  8. Stiffness matrix - Wikipedia

    en.wikipedia.org/wiki/Stiffness_matrix

    In general, to each scalar elliptic operator L of order 2k, there is associated a bilinear form B on the Sobolev space H k, so that the weak formulation of the equation Lu = f is [,] = (,) for all functions v in H k. Then the stiffness matrix for this problem is

  9. Partial trace - Wikipedia

    en.wikipedia.org/wiki/Partial_trace

    converges in the strong operator topology of L(V), it is independent of the chosen basis of W. The partial trace Tr W (T) is defined to be this operator. The partial trace of a self-adjoint operator is defined if and only if the partial traces of the positive and negative parts are defined.