Restricted normal cones and the method of alternating projections: applications

DOI10.1007/s11228-013-0238-3zbMath1349.65191OpenAlexW2041901627MaRDI QIDQ368468

Hung M. Phan, Heinz H. Bauschke, D. Russell Luke, Shawn Xianfu Wang

Publication date: 23 September 2013

Published in: Set-Valued and Variational Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11228-013-0238-3

zbMATH Keywords

normal conelinear convergenceconvex setprojection operatorFriedrichs anglemethod of alternating projectionsnonconvex setrestricted normal conesuperregularity

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonconvex programming, global optimization (90C26) Nonlinear programming (90C30) Numerical optimization and variational techniques (65K10) Nonsmooth analysis (49J52) Numerical methods based on nonlinear programming (49M37) Set-valued operators (47H04) Numerical methods of relaxation type (49M20)

Related Items (20)

On local convergence of the method of alternating projections ⋮ Linear convergence of the generalized Douglas-Rachford algorithm for feasibility problems ⋮ Restricted normal cones and the method of alternating projections: theory ⋮ Affine nonexpansive operators, Attouch-Théra duality and the Douglas-Rachford algorithm ⋮ Set regularities and feasibility problems ⋮ Restricted normal cones and sparsity optimization with affine constraints ⋮ Nonnegative low rank tensor approximations with multidimensional image applications ⋮ Transversality and alternating projections for nonconvex sets ⋮ Provable Phase Retrieval with Mirror Descent ⋮ The method of alternating relaxed projections for two nonconvex sets ⋮ On the existence of minimizers of proximity functions for split feasibility problems ⋮ About intrinsic transversality of pairs of sets ⋮ About subtransversality of collections of sets ⋮ Prox-regularity of rank constraint sets and implications for algorithms ⋮ A convergent relaxation of the Douglas-Rachford algorithm ⋮ Linear convergence of the Douglas–Rachford method for two closed sets ⋮ Metric inequality conditions on sets and consequences in optimization ⋮ Necessary conditions for linear convergence of iterated expansive, set-valued mappings ⋮ Quantitative Convergence Analysis of Iterated Expansive, Set-Valued Mappings ⋮ Linear Convergence of Projection Algorithms

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