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The article considers minimization of the expectation of convex function. Problems of this type often arise in machine learning and a variety of other applications. In practice, stochastic gradient descent (SGD) and similar procedures are usually used to solve such problems. We propose to use the ellipsoid method with mini-batching, which converges linearly and can be more efficient than SGD for a class of problems. This is verified by our experiments, which are publicly available. The algorithm does not require neither smoothness nor strong convexity of the objective to achieve linear convergence. Thus, its complexity does not depend on the conditional number of the problem. We prove that the method arrives at an approximate solution with given probability when using mini-batches of size proportional to the desired accuracy to the power −2. This enables efficient parallel execution of the algorithm, whereas possibilities for batch parallelization of SGD are rather limited. Despite fast convergence, ellipsoid method can result in a greater total number of calls to oracle than SGD, which works decently with small batches. Complexity is quadratic in dimension of the problem, hence the method is suitable for relatively small dimensionalities.

Finding the global minimum of a nonconvex function is one of the key and most difficult problems of the modern optimization. In this paper we consider special classes of nonconvex problems which have a clear and distinct global minimum.

In the first part of the paper we consider two classes of «good» nonconvex functions, which can be bounded below and above by a parabolic function. This class of problems has not been widely studied in the literature, although it is rather interesting from an applied point of view. Moreover, for such problems first-order and higher-order methods may be completely ineffective in finding a global minimum. This is due to the fact that the function may oscillate heavily or may be very noisy. Therefore, our new methods use only zero-order information and are based on grid search. The size and fineness of this grid, and hence the guarantee of convergence speed and oracle complexity, depend on the «goodness» of the problem. In particular, we show that if the function is bounded by fairly close parabolic functions, then the complexity is independent of the dimension of the problem. We show that our new methods converge with a linear convergence rate $\log(1/\varepsilon)$ to a global minimum on the cube.

In the second part of the paper, we consider the nonconvex optimization problem from a different angle. We assume that the target minimizing function is the sum of the convex quadratic problem and a nonconvex «noise» function proportional to the distance to the global solution. Considering functions with such noise assumptions for zero-order methods is new in the literature. For such a problem, we use the classical gradient-free approach with gradient approximation through finite differences. We show how the convergence analysis for our problems can be reduced to the standard analysis for convex optimization problems. In particular, we achieve a linear convergence rate for such problems as well.

Experimental results confirm the efficiency and practical applicability of all the obtained methods.

The paper studies a multidimensional convection-diffusion equation with variable coefficients and a nonclassical boundary condition. Two cases are considered: in the first case, the first boundary condition contains the integral of the unknown function with respect to the integration variable $x_\alpha^{}$, and in the second case, the integral of the unknown function with respect to the integration variable $\tau$, denoting the memory effect. Similar problems arise when studying the transport of impurities along the riverbed. For an approximate solution of the problem posed, a locally one-dimensional difference scheme by A.A. Samarskii with order of approximation $O(h^2+\tau)$. In view of the fact that the equation contains the first derivative of the unknown function with respect to the spatial variable $x_\alpha^{}$, the wellknown method proposed by A.A. Samarskii in constructing a monotonic scheme of the second order of accuracy in $h_\alpha^{}$ for a general parabolic type equation containing one-sided derivatives taking into account the sign of $r_\alpha^{}(x,t)$. To increase the boundary conditions of the third kind to the second order of accuracy in $h_\alpha^{}$, we used the equation, on the assumption that it is also valid at the boundaries. The study of the uniqueness and stability of the solution was carried out using the method of energy inequalities. A priori estimates are obtained for the solution of the difference problem in the $L_2^{}$-norm, which implies the uniqueness of the solution, the continuous and uniform dependence of the solution of the difference problem on the input data, and the convergence of the solution of the locally onedimensional difference scheme to the solution of the original differential problem in the $L_2^{}$-norm with speed equal to the order of approximation of the difference scheme. For a two-dimensional problem, a numerical solution algorithm is constructed.

A variant of the inverse method of characteristics (IMH) is presented, in whose algorithm an additional fractional time step is introduced, which makes it possible to increase the accuracy of calculations due to a more accurate approximation of the characteristics. The calculation formulas of the modified method for the equations of the one-velocity model of a gas-liquid mixture are given, with the help of which one-dimensional and also flat test problems with self-similar solutions are calculated. When solving multidimensional problems, the original system of equations is split into a number of one-dimensional subsystems, for the calculation of which the inverse method of characteristics with a fractional time step is used. Using the proposed method, the following were calculated: the one-dimensional problem of the decay of an arbitrary discontinuity in a dispersed medium; a twodimensional problem of the interaction of a homogeneous gas-liquid flow with an obstacle with an attached shock wave, as well as a flow with a centered rarefaction wave. The results of numerical calculations of these problems are compared with self-similar solutions and their satisfactory agreement is noted. On the example of the Riemann problem with a shock wave, a comparison is made with a number of conservative, non-conservative, first and higher orders of accuracy schemes, from which, in particular, it follows that the presented calculation method, i. e. MIMC, quite competitive. Despite the fact that the application of MIMC requires many times more time than the original inverse method of characteristics (IMC), calculations can be carried out with an increased time step and, in some cases, more accurate results can be obtained. It is noted that the method with a fractional time step has advantages over the IMC in cases where the characteristics of the system are significantly curvilinear. For this reason, the use of MIMC, for example, for the Euler equations is inappropriate, since for the latter the characteristics within the time step differ little from straight lines.

A nonlinear oscillatory system described by ordinary differential equations with variable coefficients is considered, in which terms that are linearly dependent on coordinates, velocities and accelerations are explicitly distinguished; nonlinear terms are written as implicit functions of these variables. For the numerical solution of the initial problem described by such a system of differential equations, the one-step Galerkin method is used. At the integration step, unknown functions are represented as a sum of linear functions satisfying the initial conditions and several given correction functions in the form of polynomials of the second and higher degrees with unknown coefficients. The differential equations at the step are satisfied approximately by the Galerkin method on a system of corrective functions. Algebraic equations with nonlinear terms are obtained, which are solved by iteration at each step. From the solution at the end of each step, the initial conditions for the next step are determined.

The corrective functions are taken the same for all steps. In general, 4 or 5 correction functions are used for calculations over long time intervals: in the first set — basic power functions from the 2nd to the 4th or 5th degrees; in the second set — orthogonal power polynomials formed from basic functions; in the third set — special linear-independent polynomials with finite conditions that simplify the “docking” of solutions in the following steps.

Using two examples of calculating nonlinear oscillations of systems with one and two degrees of freedom, numerical studies of the accuracy of the numerical solution of initial problems at various time intervals using the Galerkin method using the specified sets of power-law correction functions are performed. The results obtained by the Galerkin method and the Adams and Runge –Kutta methods of the fourth order are compared. It is shown that the Galerkin method can obtain reliable results at significantly longer time intervals than the Adams and Runge – Kutta methods.

The paper deals with a heat wave motion problem for a degenerate second-order nonlinear parabolic equation with power nonlinearity. The considered boundary condition specifies in a plane the motion equation of the circular zero front of the heat wave. A new numerical-analytical algorithm for solving the problem is proposed. A solution is constructed stepby- step in time using difference time discretization. At each time step, a boundary value problem for the Poisson equation corresponding to the original equation at a fixed time is considered. This problem is, in fact, an inverse Cauchy problem in the domain whose initial boundary is free of boundary conditions and two boundary conditions (Neumann and Dirichlet) are specified on a current boundary (heat wave). A solution of this problem is constructed as the sum of a particular solution to the nonhomogeneous Poisson equation and a solution to the corresponding Laplace equation satisfying the boundary conditions. Since the inhomogeneity depends on the desired function and its derivatives, an iterative solution procedure is used. The particular solution is sought by the collocation method using inhomogeneity expansion in radial basis functions. The inverse Cauchy problem for the Laplace equation is solved by the null field method as applied to a circular domain with a circular hole. This method is used for the first time to solve such problem. The calculation algorithm is optimized by parallelizing the computations. The parallelization of the computations allows us to realize effectively the algorithm on high performance computing servers. The algorithm is implemented as a program, which is parallelized by using the OpenMP standard for the C++ language, suitable for calculations with parallel cycles. The effectiveness of the algorithm and the robustness of the program are tested by the comparison of the calculation results with the known exact solution as well as with the numerical solution obtained earlier by the authors with the use of the boundary element method. The implemented computational experiment shows good convergence of the iteration processes and higher calculation accuracy of the proposed new algorithm than of the previously developed one. The solution analysis allows us to select the radial basis functions which are most suitable for the proposed algorithm.

A numerical method is proposed that approximates the equations of the dynamics of a weakly compressible viscous flow in the presence of a polymer component of the flow. The behavior of the flow under the influence of a static external periodic force in a periodic square cell is investigated. The methodology is based on a hybrid approach. The hydrodynamics of the flow is described by a system of Navier – Stokes equations and is numerically approximated by the linearized Godunov method. The polymer field is described by a system of equations for the vector of stretching of polymer molecules $\bf R$, which is numerically approximated by the Kurganov – Tedmor method. The choice of model relationships in the development of a numerical methodology and the selection of modeling parameters made it possible to qualitatively model and study the regime of elastic turbulence at low Reynolds $Re \sim 10^{-1}$. The polymer solution flow dynamics equations differ from the Newtonian fluid dynamics equations by the presence on the right side of the terms describing the forces acting on the polymer component part. The proportionality coefficient $A$ for these terms characterizes the backward influence degree of the polymers number on the flow. The article examines in detail how the flow and its characteristics change depending on the given coefficient. It is shown that with its growth, the flow becomes more chaotic. The flow energy spectra and the spectra of the polymers stretching field are constructed for different values of $A$. In the spectra, an inertial sub-range of the energy cascade is traced for the flow velocity with an indicator $k \sim −4$, for the cascade of polymer molecules stretches with an indicator $−1.6$.

This article is dedicated to use of S-spline theory for solving equations in partial derivatives. For example, we consider solution of the Poisson equation. S-spline — is a piecewise-polynomial function. Its coefficients are defined by two states. The first part of coefficients are defined by smoothness of the spline. The second coefficients are determined by least-squares method. According to order of considered polynomial and number of conditions of first and second type we get S-splines with different properties. At this moment we have investigated order 3 S-splines of class C¹ and order 5 S-splines of class C² (they meet conditions of smoothness of order 1 and 2 respectively). We will consider how the order 3 S-splines of class C¹ can be applied for solving equation of Poisson on circle and other areas.

The semiclassical approximation method is applied for solution construction of the Fokker–Planck equation with quadratic nonlocal nonlinearity and various coefficients in models of asset returns estimation. Analitical expressions determining nonlinear evolution operator are obtained in semiclasical approximation.

The approach given in this work helps to organize the operative control over action intensity of pollution emissions in atmosphere. The approach allows to sequential estimate of unknown intensity of atmospheric pollution source on the base of concentration measurements of impurity in several stationary control points is offered in the work. The inverse problem was solved by means of the step-by-step regularization and the sequential function specification method. The solution is presented in the form of the digital filter in terms of Hamming. The fitting algorithm of regularization parameter r for function specification method is described.