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Two features distinguish the Bayesian approach to learning models from data. First, beliefs derived from background knowledge are used to select a prior probability distribution for the model parameters. Second, predictions of future observations are made by integrating the model's predictions with respect to the posterior parameter distribution obtained by(More)
Under the assumption that the incidence matrix of a 2-(45; 12; 3) design has a certain block structure, we determine completely the number of non-isomorphic designs involved. We discover 1136 such designs with trivial automorphism group. In addition we analyze all 2-(45; 12; 3) designs having an automorphism of order 5 or 11. Altogether, the total number of(More)
Formulas developed originally by Weierstrass have been used since the 1960s by many others for the simultaneous determination of all the roots of a polynomial. Convergence to simple roots is quadratic, but individual approximations to a multiple root converge only linearly. However, it is shown here that the mean of such individual approximations converges(More)
Formulas developed originally by Weierstrass have been used since the 1960's by many others for the simultaneous determination of all the roots of a polynomial. Convergence to simple roots is quadratic, but individual approximations to a multiple root converge only linearly. However, it is shown here that the mean of such individual approximations converges(More)
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