On Proximal Algorithms with Inertial Effects Beyond Monotonicity

IF 1.4 4区 数学 Q2 MATHEMATICS, APPLIED Numerical Functional Analysis and Optimization Pub Date : 2023-10-13 DOI:10.1080/01630563.2023.2266762
Alfredo N. Iusem, R. T. Marcavillaca
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Abstract

AbstractInertial procedures attached to classical methods for solving monotone inclusion and optimization problems, which arise from an implicit discretization of second-order differential equations, have shown a remarkable acceleration effect with respect to these classical algorithms. Among these classical methods, one can mention steepest descent, alternate directions, and the proximal point methods. For the problem of finding zeroes of set-valued operators, the convergence analysis of all existing inertial-proximal methods requires the monotonicity of the operator. We present here a new inertial-proximal point algorithm for finding zeroes of set-valued operators, whose convergence is established for a relevant class of nonmonotone operators, namely the hypomonotone ones.KEYWORDS: Generalized monotone operatorshypomonotone operatorsinertial methodsproximal point methodMATHEMATICS SUBJECT CLASSIFICATION: 90C2590C3047H05
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超越单调性的惯性效应的近端算法
求解二阶微分方程隐式离散化引起的单调包含和优化问题的经典方法所附的积分过程,相对于这些经典算法显示出显著的加速效应。在这些经典方法中,可以提到最陡下降法、交替方向法和近点法。对于集值算子的寻零问题,现有的所有积分逼近方法的收敛性分析都要求算子的单调性。本文提出了一种求集值算子零点的新算法,该算法对一类相关的非单调算子即次单调算子证明了收敛性。关键词:广义单调算子;拟单调算子;正弦方法;近似点法
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来源期刊
CiteScore
2.40
自引率
8.30%
发文量
74
审稿时长
6-12 weeks
期刊介绍: Numerical Functional Analysis and Optimization is a journal aimed at development and applications of functional analysis and operator-theoretic methods in numerical analysis, optimization and approximation theory, control theory, signal and image processing, inverse and ill-posed problems, applied and computational harmonic analysis, operator equations, and nonlinear functional analysis. Not all high-quality papers within the union of these fields are within the scope of NFAO. Generalizations and abstractions that significantly advance their fields and reinforce the concrete by providing new insight and important results for problems arising from applications are welcome. On the other hand, technical generalizations for their own sake with window dressing about applications, or variants of known results and algorithms, are not suitable for this journal. Numerical Functional Analysis and Optimization publishes about 70 papers per year. It is our current policy to limit consideration to one submitted paper by any author/co-author per two consecutive years. Exception will be made for seminal papers.
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