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PART I: Probability and Statistics, I. Rodionov, On threshold selection problem for extremal index estimation.- D. F. Kuznetsov and M. D. Kuznetsov, Mean-Square Approximation of Iterated Stochastic Integrals from Strong Exponential Milstein and Wagner–Platen Methods for NonCommutative Semilinear SPDEs Based on Multiple Fourier–Legendre Series.- M. Zhitlukhin, A sequential test for the drift of a Brownian motion with a possibility to change a decision.- T. Belkina, Survival Probabilities in Compound Poisson Model with Negative Claims and Investments as Viscosity Solutions of Integro-Differential Equations.- M. L. Esqu´ıvel, N. Machado, N. P. Krasii, P. P. Mota, On the Information Content of some Stochastic Algorithms.- V. Khatskevich, On modification of the law of large numbers and linear regression of fuzzy random variables.- B. Yana, Stochastic approach to the vanishing viscosity method.- E. Burnaev, Generalization Bound for Imbalanced Classification.- A. Lykov, V. Malyshev, M. Melikian, and A. Zamyatin, Resonance in Large Finite Particle Systems.- A. I. Zhdanok, Cycles in Spaces of Finitely Additive Measures of General Markov Chains. E. Yarovaya, D. Balashova, I. KhristolyubovIV, Branching Walks with a Finite Set of Branching Sources and Pseudo-Sources.- E. Pchelintsev, S. Pergamenshchikov, Efficient Improved Estimation Method for non-Gaussian Regression from Discrete Data.- S. Bobkov, A. Naumov, V. Ulyanov, Two–sided bounds for PDF’s maximum of a sum of weighted chi-square variables.- Y. A. Demidovich and D. A. Shabanov, On the chromatic number of a random 3-uniform hypergraph.- V. Melas and D. Salnikov, On asymptotic power of the new test for equality of two distributions.- G. Christoph and V. V. Ulyanov, Random Dimension Low Sample Size Asymptotics.- P. Yaskov, Limit of the smallest eigenvalue of a sample covariance matrix for spherical and related distributions.- A. Veretennikov, On positive recurrence of one-dimensional diffusions with independent switching In memory of Svetlana Anulova (19.10.1952 – 21.11.2020).- PART - II: Applications of Stochastic Methods, Y. Makarova, V. Kutsenko, E. Yarovaya, On Two-Type Branching Random Walks and Their Applications for Genetic Modelling.- A. V. Kryanev, V. V. Ivanov, L. A. Sevastyanov, and D. K. Udumyan, Reconstruction of multivariable functions under uncertainty by means of the scheme of metric analysis.- A. Nazarov, T. Phung-Duc, S. Paul, and O. Lizyura, Diffusion Approximation for Retrial Queue with Two-Way Communication and Renewal Input.- V. A. Galkin and A. V. Makarenko, Application of deep learning methods for the identification of partially observable subgraphs under the conditions of a priori uncertainty and stochastic disturbances (using the example of the problem of recognizing constellations).-  V. Rusev, A. Skorikov, Residual life time of the Gnedenko extreme - value distributions, asymptotic behavior and applications.- E. Alymova, O. Kudryavtsev, The application of a neural network and elements of regression analysis in the development of a methodology for effective foreign exchange trading.- E. Bashtova and E. Lenena, Statistical analysis of generalized Jackson network with unreliable servers via strong approximation.- Korol E.A., Afanasyev G.A., Applications of vacation queues with close-down time to Maintenance of Residential Buildings.- I. L. Lapatin and A. A. Nazarov, Output Process of Retrial Queue with Two-Way Communication under Low Rate of Retrials Limit Condition.- K. Samouylov, V. Naumov, Stochastic lists of multiple resources.- Author Index.

Albert N. Shiryaev is a Chief Scientific Researcher at Steklov Mathematical Institute of the Russian Academy of Sciences and the Head of the Probability Theory Department of the Faculty of Mechanics and Mathematics at Lomonosov Moscow State University. He is a Full Member of the Russian Academy of Sciences and the recipient of many honours and awards, including the Markov Prize in 1974, the Kolmogorov Prize in 1994, and the Chebyshev Medal of the Russian Academy of Science in 2017. His numerous other books include Probability [translated by Dmitry M. Chibisov], Limit Theorems for Stochastic Processes [with Jean Jacod], Optimal Stopping Rules [translated by A.B. Aries], Stochastic Disorder Problems [translated by Andrei Iacob], and Statistics of Random Processes [with Robert S. Liptser].<div><br></div><div>Konstantin Samouylov received his PhD in Probability Theory from the Moscow State University, in 1985, and a Full Doctor of Sciences degree in Telecommunications from the Moscow Technical University of Communications and Informatics in 2005. In 1985–1996, he held several positions at the Faculty of Science of the Peoples' Friendship University of Russia (RUDN University), where he became a head of Telecommunications System Department in 1996. Since 2014, he has been the head of the Applied Probability and Informatics Department, and since 2017, he has also held the position of Director of Applied Mathematics and Communications Technology Institute (IAM&CT) at RUDN University. He was visiting professor/professor-research at Lappeenranta University of Technology and Helsinki University of Technology (Aalto), Finland; Moscow Technical University of Telecommunications and Informatics, Russia; Moscow International Higher Business School (Mirbis), Russia; and University of Pisa, Italy. He was a member of the ITU-T SG11 and IFIP TC6 WG 6.7. He has worked in a number of R&D projects within different frameworks, e.g., COST IRACON, projects of Russian Foundation for Basic Research (RFBR), TEKES (Finland) and companies including Nokia, Telecom Finland, VTT, Rostelecom, etc. He is a member of editorial boards and reviewer of several scientific journals, and he is co-chair and TPC member of several international conferences. His current research interests include applied aspects of Probability Theory and Stochastic Processes,&nbsp;Queuing&nbsp;and teletraffic theory, performance analysis of 5G/5G+ networks, resource allocation in heterogeneous wireless networks, social networks, and big data analysis. He has authored and co-authored over 150 scientific and conference papers and six books. Prof. Samouylov’s honors include the 2018 IEEE GLOBECOM Conference Best Paper Award.</div><div><br></div><div><p>Dmitry&nbsp;V. Kozyrev&nbsp;received his Ph.D. degree in Physics and Mathematics in 2013. Since 2007, he has been working at the Department of Probability Theory and Mathematical Statistics of the Peoples' Friendship University of Russia (RUDN University). Since2013, he is an Associate Professor at the Department of Applied Probability and Informatics (RUDN University) and a Senior Research Fellow at the V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Moscow, Russia. He is a member of the reviewer board of several scientific journals, as well as proceedings editor and member of organizing / program committee of several international conferences. His current research activities include Stochastic Modeling, Reliability Assessment and Performance analysis, Sensitivity analysis, Modeling and Simulation of repairable systems, Applied Probability. He has authored and co-authored over 80 published papers.</p><p></p><p><br></p><br></div>

<p>Highlighting the latest advances in&nbsp;stochastic analysis and its applications, this volume collects carefully selected and peer-reviewed papers from the 5th International Conference on Stochastic Methods (ICSM-5), held in Moscow, Russia, November 23-27, 2020. The contributions deal with diverse topics such as stochastic analysis, stochastic methods in computer science, analytical modeling, asymptotic methods and limit theorems, Markov processes, martingales, insurance and financial mathematics, queueing theory and stochastic networks, reliability theory, risk analysis, statistical methods and applications, machine learning and data analysis. The 29 articles in this volume are a representative sample of the 87 high-quality papers accepted and presented during the conference. The aim of the ICSM-5 conference is to promote the collaboration of researchers from Russia and all over the world, and to contribute to the development of the field of stochastic analysis and applications ofstochastic models.<br></p>

Contains novel and important results in Stochastic Analysis Presents contributions from eminent researchers Useful for mathematicians, engineers and postgraduate students