Proximal point methodQuasiconvex functionHadamard manifoldsNonsmooth optimizationAbstract subdifferentialIn this paper we present two inexact proximal point algorithms to solve minimization problems for quasiconvex objective functions on Hadamard manifolds.We prove that under natural assumptions the sequence generate...
proximal point method, in the case that the objective function is nonsmooth and nonconvex, and the subproblems are determined by a quasi distance which ... GC Bento,JXDC Neto,PR Oliveira - 《Mathematics》 被引量: 13发表: 2011年 An inexact proximal point method for solving generalized fraction...
This paper analyzes the iteration-complexity of a quadratic penalty accelerated inexact proximal point method for solving linearly constrained nonconvex co... W Kong,JG Melo,RDC Monteiro - 《Siam Journal on Optimization》 被引量: 5发表: 2018年 Proximal Point Algorithms on Hadamard Manifolds: Linear...
Some error bounds are derived using both merit functions for the corresponding formulations of the proximal subproblem. We further use the regularized gap function to devise a new inexact proximal point algorithm for solving monotone variational inequalities. This inexact proximal point method preserves ...
Thesaurus in·ex·act (ĭn′ĭg-zăkt′) adj. 1.Not strictly accurate or precise; not exact:an inexact quotation; an inexact description of what had taken place. 2.Not rigorous or meticulous:an inexact mind; an inexact method.
The proximal-point algorithm, introduced by Martinet (Ref. and since the projector P is easy toevaluate at each iteration, the main task of the algorithm is to design inexact self-adaptivealgorithms with relative error tolerance and constant adjustment parameter is thus desirable. Variational inequali...
On the Convergence Analysis of Inexact Proximal Point Algorithms for Maximal Strongly Monotone Operators 关于极大强单调算子的不精确邻近点算法的收敛性分析 CENG Liu-Chuan,曾六川 Keywords: Proximal point algorithm,Maximal strongly monotone operator,Inexact method邻近点算法,极大强单调算子,不精确方法 Full-Text...
General Proximal Gradient Method: A Case for Non-Euclidean Norms In this paper, we consider composite convex minimization problems. We advocate the merit of considering Generalized Proximal gradient Methods (GPM) where the norm employed is not Euclidean. To that end, we show the tractability of th...
In this paper, we propose a second order interior point algorithm for symmetric cone programming using a wide neighborhood of the central path. The converg... Jian,ZhangKecun,Zhang - 《Mathematical Methods of Operations Research》 被引量: 23发表: 2011年 An extended interior-point method for tr...
Algorithm 2.1 The Inexact Newton-Like Method with Non-Monotone Search for Low-Rank and Sparse Matrix Recovery Input: PΩ(D), U0∈Rm×r, V0∈Rr×n, U,V are non-singular matrices, integer l≥0, sparsity parameter α, S0∈Rm×n with ‖S0‖0≤α|Ω|;0<β<12; Step 1. Uk+1=(P...