The second issue of the journal Computer Research and Modeling (Scopus Q2) has appeared (Volume 15). It was prepared by the staff of the MMO laboratory. You can get acquainted with the materials by following the link.

Release topics of articles:

1. Boris Polyak — path in science. Optimization (Gasnikov A. V.)

2. Numerical solving of an inverse problem of a hyperbolic heat equation with small parameter (Akindinov G. D., Matyukhin V. V., Krivorotko O. I.)

3. Influence of the mantissa finiteness on the accuracy of gradient-free optimization methods (Vostrikov D. D., Konin G. O., Lobanov A. V., Matyukhin V. V)

4. Application of discrete multicriteria optimization methods for the digital predistortion model design (Maslovskiy A. Yu., Sumenkov O. Yu., Vorkutov D. A., Chukanov S. V)

5. On the modification of the method of component descent for solving some inverse problems of mathematical physics (Pletnev N. V., Matyukhin V. V)

6. Transport modeling: averaging price matrices (Podlipnova I. V., Persiianov M. I., Shvetsov V. I., Gasnikova E. V)

7. Survey of convex optimization of Markov decision processes (Rudenko V. D., Yudin N. E., Vasin A. A.)

8. The model of two-level intergroup competition (Samoylenko I. A., Kuleshov I. V., Raigorodskii A. M.)

9. Experimental comparison of PageRank vector calculation algorithms (Skachkov D. A., Gladyshev S. G., Raigorodskii A. M.)

10. Comparsion of stochastic approximation and sample average approximation for saddle point problem with bilinear coupling term (Skorik S. N., Pirau V. V., Sedov S. A., Dvinskikh D. M.)

11. Subgradient methods for weakly convex and relatively weakly convex problems with a sharp minimum (Stonyakin F. S., Ablaev S. S., Baran I. V., Alkousa M. S.)

12. Analogues of the relative strong convexity condition for relatively smooth problems and adaptive gradient-type methods (Stonyakin F. S., Savchuk O. S., Baran I. V., Alkousa M. S., Titov A. A.)

13. On Accelerated methods for saddle-point problems with composite structure (Tominin Y. D., Tominin V. D., Borodich E. D., Kovalev D. A., Dvurechensky P. E., Gasnikov A. V., Chukanov S. V)

14. Nonsmooth distributed min-max optimization using the smoothing technique (Chen J., Lobanov A. V., Rogozin A. V)

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