全部文献期刊学位论文会议报纸专利标准年鉴图书|学者科研项目
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作者:Haishu Lu , Zhihua Wang
来源:[J].Journal of Inequalities and Applications(IF 0.822), 2017, Vol.2017 (1)Springer
摘要:This paper deals with the abstract generalized vector quasi-equilibrium problem in noncompact Hadamard manifolds. We prove the existence of solutions to the abstract generalized vector quasi-equilibrium problem under suitable conditions and provide applications to an abstract vec...
作者:Jinbao Jian , Hanjun Zeng , Guodong Ma ...
来源:[J].Journal of Inequalities and Applications(IF 0.822), 2017, Vol.2017 (1)Springer
摘要:In this paper, a class of nonlinear constrained optimization problems with both inequality and equality constraints is discussed. Based on a simple and effective penalty parameter and the idea of primal-dual interior point methods, a QP-free algorithm for solving the discussed pr...
作者:Ademir A. Ribeiro , Mael Sachine , Sandra A. Santos
来源:[J].Computational and Applied Mathematics(IF 0.413), 2017, Vol.36 (3), pp.1255-1272Springer
摘要:In the context of sequential methods for solving general nonlinear programming problems, it is usual to work with augmented subproblems instead of the original ones. This paper addresses the theoretical reasoning behind handling the original subproblems by an augmentation strateg...
作者:Xiaojing Zhu
来源:[J].Computational Optimization and Applications(IF 1.278), 2017, Vol.67 (1), pp.73-110Springer
摘要:In this paper we propose a new Riemannian conjugate gradient method for optimization on the Stiefel manifold. We introduce two novel vector transports associated with the retraction constructed by the Cayley transform. Both of them satisfy the Ring-Wirth nonexpansive conditi...
作者:Frank E. Curtis , Arvind U. Raghunathan
来源:[J].Computational Optimization and Applications(IF 1.278), 2017, Vol.67 (2), pp.317-360Springer
摘要:An algorithm for solving nearly-separable quadratic optimization problems (QPs) is presented. The approach is based on applying a semismooth Newton method to solve the implicit complementarity problem arising as the first-order stationarity conditions of such a QP. An import...
作者:Zhaosong Lu , Yong Zhang , Jian Lu
来源:[J].Computational Optimization and Applications(IF 1.278), 2017, Vol.68 (3), pp.619-642Springer
摘要:In this paper we study the \(\ell _p\) (or Schatten- p quasi-norm) regularized low-rank approximation problems. In particular, we introduce a class of first-order stationary points for them and show that any local minimizer of these problems must be a first-order stationary point...
作者:Daniel O’Connor , Lieven Vandenberghe
来源:[J].Computational Optimization and Applications(IF 1.278), 2017, Vol.67 (3), pp.521-541Springer
摘要:Image deblurring techniques based on convex optimization formulations, such as total-variation deblurring, often use specialized first-order methods for large-scale nondifferentiable optimization. A key property exploited in these methods is spatial invariance of the blurrin...
作者:Biao Qu , Changyu Wang , Naihua Xiu
来源:[J].Computational Optimization and Applications(IF 1.278), 2017, Vol.67 (1), pp.175-199Springer
摘要:In this paper, based on a merit function of the split feasibility problem (SFP), we present a Newton projection method for solving it and analyze the convergence properties of the method. The merit function is differentiable and convex. But its gradient is a linear composite func...
作者:J. C. De Los Reyes , E. Loayza , P. Merino
来源:[J].Computational Optimization and Applications(IF 1.278), 2017, Vol.67 (2), pp.225-258Springer
摘要:We present a second order algorithm, based on orthantwise directions, for solving optimization problems involving the sparsity enhancing \(\ell _1\) -norm. The main idea of our method consists in modifying the descent orthantwise directions by using second order information both ...
作者:Stefania Bellavia , Lapo Governi , Alessandra Papini ...
来源:[J].Mediterranean Journal of Mathematics(IF 0.641), 2017, Vol.14 (3)Springer
摘要:Shape from shading (SFS) denotes the problem of reconstructing a 3D surface, starting from a single shaded image which represents the surface itself. Minimization techniques are commonly used for solving the SFS problem, where the objective function is a weighted combination...

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