A block symmetric Gauss–Seidel decomposition theorem for convex composite quadratic programming and its applications
نویسندگان
چکیده
منابع مشابه
A block symmetric Gauss-Seidel decomposition theorem for convex composite quadratic programming and its applications
For a symmetric positive semidefinite linear system of equations Qx = b, where x = (x1, . . . , xs) is partitioned into s blocks, with s ≥ 2, we show that each cycle of the classical block symmetric Gauss-Seidel (block sGS) method exactly solves the associated quadratic programming (QP) problem but added with an extra proximal term of the form 12‖x−x ‖T , where T is a symmetric positive semidef...
متن کاملA simplicial decomposition framework for large scale convex quadratic programming
In this paper, we analyze in depth a simplicial decomposition like algorithmic framework for large scale convex quadratic programming. In particular, we first propose two tailored strategies for handling the master problem. Then, we describe a few techniques for speeding up the solution of the pricing problem. We report extensive numerical experiments on both real portfolio optimization and gen...
متن کاملConstruction of Hexahedral Block Topology and its Decomposition to Generate Initial Tetrahedral Grids for Aerodynamic Applications
Making an initial tetrahedral grid for complex geometry can be a tedious and time consuming task. This paper describes a novel procedure for generation of starting tetrahedral cells using hexahedral block topology. Hexahedral blocks are arranged around an aerodynamic body to form a flow domain. Each of the hexahedral blocks is then decomposed into six tetrahedral elements to obtain an initial t...
متن کاملA Recurrent Neural Network for Solving Strictly Convex Quadratic Programming Problems
In this paper we present an improved neural network to solve strictly convex quadratic programming(QP) problem. The proposed model is derived based on a piecewise equation correspond to optimality condition of convex (QP) problem and has a lower structure complexity respect to the other existing neural network model for solving such problems. In theoretical aspect, stability and global converge...
متن کاملA Limit Theorem for Quadratic Forms and Its Applications
We consider quadratic forms of martingale differences and establish a central limit theorem under mild and easily verifiable conditions+ By approximating Fourier transforms of stationary processes by martingales, our central limit theorem is applied to the smoothed periodogram estimate of spectral density functions+ Our results go beyond earlier ones by allowing a variety of nonlinear time seri...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Mathematical Programming
سال: 2018
ISSN: 0025-5610,1436-4646
DOI: 10.1007/s10107-018-1247-7