Ergodic convergence of a stochastic proximal point algorithm

نویسنده

  • Pascal Bianchi
چکیده

The purpose of this paper is to establish the almost sure weak ergodic convergence of a sequence of iterates (xn) given by xn+1 = (I + λnA(ξn+1, . )) (xn) where (A(s, . ) : s ∈ E) is a collection of maximal monotone operators on a separable Hilbert space, (ξn) is an independent identically distributed sequence of random variables on E and (λn) is a positive sequence in l\l. The weighted averaged sequence of iterates is shown to converge weakly to a zero (assumed to exist) of the Aumann expectation E(A(ξ1, . )) under the assumption that the latter is maximal. We consider applications to stochastic optimization problems of the form minE(f(ξ1, x)) w.r.t. x ∈ m ⋂

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

W-convergence of the proximal point algorithm in complete CAT(0) metric spaces

‎In this paper‎, ‎we generalize the proximal point algorithm to complete CAT(0) spaces and show‎ ‎that the sequence generated by the proximal point algorithm‎ $w$-converges to a zero of the maximal‎ ‎monotone operator‎. ‎Also‎, ‎we prove that if $f‎: ‎Xrightarrow‎ ‎]-infty‎, +‎infty]$ is a proper‎, ‎convex and lower semicontinuous‎ ‎function on the complete CAT(0) space $X$‎, ‎then the proximal...

متن کامل

A Hybrid Proximal Point Algorithm for Resolvent operator in Banach Spaces

Equilibrium problems have many uses in optimization theory and convex analysis and which is why different methods are presented for solving equilibrium problems in different spaces, such as Hilbert spaces and Banach spaces. The purpose of this paper is to provide a method for obtaining a solution to the equilibrium problem in Banach spaces. In fact, we consider a hybrid proximal point algorithm...

متن کامل

A first-order stochastic primal-dual algorithm with correction step

We investigate the convergence properties of a stochastic primal-dual splitting algorithm for solving structured monotone inclusions involving the sum of a cocoercive operator and a composite monotone operator. The proposed method is the stochastic extension to monotone inclusions of a proximal method studied in [26, 35] for saddle point problems. It consists in a forward step determined by the...

متن کامل

On the Convergence Analysis of Gravitational Search Algorithm

Gravitational search algorithm (GSA) is one of the newest swarm based optimization algorithms, which has been inspired by the Newtonian laws of gravity and motion. GSA has empirically shown to be an efficient and robust stochastic search algorithm. Since introducing GSA a convergence analysis of this algorithm has not yet been developed. This paper introduces the first attempt to a formal conve...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • SIAM Journal on Optimization

دوره 26  شماره 

صفحات  -

تاریخ انتشار 2016