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On rate of convergence in distribution of asymptotically normal statistics based on samples of random sizeIn the present paper we prove a general theorem which gives the rates of convergence
A strongly convergent combined relaxation method in hilbert spaces for strong convergence. Here, we relax this condition and show strong convergence of such a method, when
A method of bi-coordinate variations with tolerances and its convergence optimization problems. We establish its convergence and rate of convergence under rather mild assumptions.
On the convergence of combined relaxation methods for variational inequalities. The conditions under which the proposed methods attain linear convergence or terminate with a solution are also
Gradient methods with regularization for constrained optimization problems and their complexity estimates in Hilbert spaces. Usually, the custom methods attain only weak convergence. We prove strong convergence
Quadratures with super power convergence. For infinitely smooth integrand functions, the convergence law becomes super power. It is significantly faster
Convergence in Measure and τ-Compactness of τ-Measurable Operators, Affiliated with a Semifinite von Neumann Algebra of this criterion for the τ-compact case. In terms of measure convergence topology, the criterion of τ
Ethical Principles of Journalism Communication: Media Convergence as a Transforming Factor principles of journalism in the second half of the 20th century. However, the process of media convergence
Theory of spectral sequences. I, as well as the first derived limits, e.g., varinjlim{}^1. Then he introduces various kinds of convergences
Probability models for assessing effectiveness of advertising channels in the internet environmentProbability models for assessing effectiveness of advertising channels in the internet environment
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