A Class of Inexact Variable Metric Proximal Point Algorithms
نویسندگان
چکیده
منابع مشابه
A Class of Inexact Variable Metric Proximal Point Algorithms
For the problem of solving maximal monotone inclusions, we present a rather general class of algorithms, which contains hybrid inexact proximal point methods as a special case and allows for the use of a variable metric in subproblems. The global convergence and local linear rate of convergence are established under standard assumptions. We demonstrate the advantage of variable metric implement...
متن کاملInexact and accelerated proximal point algorithms
We present inexact accelerated proximal point algorithms for minimizing a proper lower semicontinuous and convex function. We carry on a convergence analysis under different types of errors in the evaluation of the proximity operator, and we provide corresponding convergence rates for the objective function values. The proof relies on a generalization of the strategy proposed in [14] for genera...
متن کاملError bounds for proximal point subproblems and associated inexact proximal point algorithms
We study various error measures for approximate solution of proximal point regularizations of the variational inequality problem, and of the closely related problem of finding a zero of a maximal monotone operator. A new merit function is proposed for proximal point subproblems associated with the latter. This merit function is based on Burachik-Iusem-Svaiter’s concept of ε-enlargement of a max...
متن کاملA family of variable metric proximal methods
We consider conceptual optimization methods combining two ideas: the Moreau-Yosida regularization in convex analysis, and quasi-Newton approximations of smooth functions. We outline several approaches based on this combination, and establish their global convergence. Then we study theoretically the local convergence properties of one of these approaches, which uses quasi-Newton updates of the o...
متن کاملSelf-adaptive inexact proximal point methods
We propose a class of self-adaptive proximal point methods suitable for degenerate optimization problems where multiple minimizers may exist, or where the Hessian may be singular at a local minimizer. If the proximal regularization parameter has the form μ(x)= β‖∇f (x)‖η where η ∈ [0,2) and β > 0 is a constant, we obtain convergence to the set of minimizers that is linear for η= 0 and β suffici...
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: SIAM Journal on Optimization
سال: 2008
ISSN: 1052-6234,1095-7189
DOI: 10.1137/070688146