Funding Information Russian Science Foundation, Grant/Award Number: 14-31-00024 Summary The paper studies numerical properties of LU and incomplete LU factorizations applied to the discrete linearized incompressible Navier–Stokes problem also known as the Oseen problem. A commonly used stabilized Petrov–Galerkin finite element method for the Oseen problem leads to the system of algebraic equati...

Solving a system of linear equations i s a key problem in engineering and science. Matrix factorization is a key component of many methods used to solve such equations. However, the factorization process is very time consuming, so these problems have often been targeted for parallel machines rather than sequential ones. Nevertheless, commercially available supercomputers are expensive and only ...

In this paper we give a lifting factorization of any matrix of order 3 or 4 whose determinant is equal to one. In the case of matrices of order 4, the factorization has been obtained by solving a system of algebraic equations, thanks to a Gröbner basis computation. The lifting factorization associated with rounding allows to construct a transformation that maps integers to integers and that is ...

Given a sparse, symmetric positive definite matrix C and an associated sparse Cholesky factorization LDL, we develop sparse techniques for updating the factorization after a symmetric modification of a row and column of C. We show how the modification in the Cholesky factorization associated with this rank-2 modification of C can be computed efficiently using a sparse rank-1 technique developed...

We describe a new parallel solver in the class of partition methods for general, nonsingular tridiagonal linear systems. Starting from an already known partitioning of the coefficient matrix among the parallel processors, we define a factorization, based on the QR factorization, which depends on the conditioning of the sub-blocks in each processor. Moreover, also the reduced system, whose solut...

Recommender system has attracted lots of attentions since it helps users alleviate the information overload problem. Matrix factorization technique is one of the most widely employed collaborative filtering techniques in the research of recommender systems due to its effectiveness and efficiency in dealing with very large user-item rating matrices. Recently, based on the intuition that addition...

This paper describes a domain-based multilevel block ILU preconditioner (BILUTM) for solving general sparse linear systems. This preconditioner combines a high accuracy incomplete LU factorization with an algebraic multilevel recursive reduction. Thus, in the first level the matrix is permuted into a block form using (block) independent set ordering and an ILUT factorization for the reordered m...

A distributed optimal control problem with the constraint of a linear elliptic partial differential equation is considered. A necessary optimality condition for this problem forms a saddle point system, the efficient and accurate solution of which is crucial. A new factorization of the Schur complement for such a system is proposed and its characteristics discussed. The factorization introduces...

In this study of the nonlinear H∞-optimal control design for strict-feedback nonlinear systems our objective is to construct globally stabilizing control laws to match the optimal control law up to any desired order, and to be inverse optimal with respect to some computable cost functional. Our recursive construction of a cost functional and the corresponding solution to the Hamilton-Jacobi-Isa...

We study the stability vis a vis adversarial noise of matrix factorization algorithm for matrix completion. In particular, our results include: (I) we bound the gap between the solution matrix of the factorization method and the ground truth in terms of root mean square error; (II) we treat the matrix factorization as a subspace fitting problem and analyze the difference between the solution su...