Wide interval for efficient self-scaling quasi-Newton algorithms
نویسندگان
چکیده
منابع مشابه
Wide interval for efficient self-scaling quasi-Newton algorithms
This paper uses certain conditions for the global and superlinear convergence of the two-parameter self-scaling Broyden family of quasi-Newton algorithms for unconstraiend optimization to derive a wide interval for self-scaling updates. Numerical testing shows that such algorithms not only accelerate the convergence of the (unscaled) methods from the so-called convex class, but increase their c...
متن کاملSelf-Scaling Parallel Quasi-Newton Methods
In this paper, a new class of self-scaling quasi-Newton(SSQN) updates for solving unconstrained nonlinear optimization problems(UNOPs) is proposed. It is shown that many existing QN updates can be considered as special cases of the new family. Parallel SSQN algorithms based on this class of class of updates are studied. In comparison to standard serial QN methods, proposed parallel SSQN(SSPQN) ...
متن کاملAnalysis of a self-scaling quasi-Newton method
We study the self-scaling BFGS method of Oren and Luenberger (1974) for solving unconstrained optimization problems. For general convex functions, we prove that the method is globally convergent with inexact line searches. We also show that the directions generated by the self-scaling BFGS method approach Newton's direction asymptotically. This would ensure superlinear convergence if, in additi...
متن کاملQuasi-Newton Methods for Nonconvex Constrained Multiobjective Optimization
Here, a quasi-Newton algorithm for constrained multiobjective optimization is proposed. Under suitable assumptions, global convergence of the algorithm is established.
متن کاملA quasi-Newton acceleration for high-dimensional optimization algorithms
In many statistical problems, maximum likelihood estimation by an EM or MM algorithm suffers from excruciatingly slow convergence. This tendency limits the application of these algorithms to modern high-dimensional problems in data mining, genomics, and imaging. Unfortunately, most existing acceleration techniques are ill-suited to complicated models involving large numbers of parameters. The s...
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: Optimization Methods and Software
سال: 2005
ISSN: 1055-6788,1029-4937
DOI: 10.1080/10556780410001709448