Linear convergence of the generalized Douglas–Rachford algorithm for feasibility problems
نویسندگان
چکیده
منابع مشابه
investigating the feasibility of a proposed model for geometric design of deployable arch structures
deployable scissor type structures are composed of the so-called scissor-like elements (sles), which are connected to each other at an intermediate point through a pivotal connection and allow them to be folded into a compact bundle for storage or transport. several sles are connected to each other in order to form units with regular polygonal plan views. the sides and radii of the polygons are...
On the Convergence of the Generalized Linear Least Squares Algorithm
This paper considers the issue of parameter estimation for biomedical applications using nonuniformly sampled data. The generalized linear least squares (GLLS) algorithm, first introduced by Feng and Ho (1993), is used in the medical imaging community for removal of bias when the data defining the model are correlated. GLLS provides an efficient iterative linear algorithm for the solution of th...
متن کاملthe algorithm for solving the inverse numerical range problem
برد عددی ماتریس مربعی a را با w(a) نشان داده و به این صورت تعریف می کنیم w(a)={x8ax:x ?s1} ، که در آن s1 گوی واحد است. در سال 2009، راسل کاردن مساله برد عددی معکوس را به این صورت مطرح کرده است : برای نقطه z?w(a)، بردار x?s1 را به گونه ای می یابیم که z=x*ax، در این پایان نامه ، الگوریتمی برای حل مساله برد عددی معکوس ارانه می دهیم.
15 صفحه اولImproved infeasible-interior-point algorithm for linear complementarity problems
We present a modified version of the infeasible-interior- We present a modified version of the infeasible-interior-point algorithm for monotone linear complementary problems introduced by Mansouri et al. (Nonlinear Anal. Real World Appl. 12(2011) 545--561). Each main step of the algorithm consists of a feasibility step and several centering steps. We use a different feasibility step, which tar...
متن کاملglm2: Fitting Generalized Linear Models with Convergence Problems
The R function glm uses step-halving to deal with certain types of convergence problems when using iteratively reweighted least squares to fit a generalized linear model. This works well in some circumstances but non-convergence remains a possibility, particularly with a nonstandard link function. In some cases this is because step-halving is never invoked, despite a lack of convergence. In oth...
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: Journal of Global Optimization
سال: 2018
ISSN: 0925-5001,1573-2916
DOI: 10.1007/s10898-018-0654-x