Proximal point algorithms for nonsmooth convex optimization with fixed point constraints
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Publication:323195
DOI10.1016/j.ejor.2016.02.057zbMath1346.90663arXiv1602.01932OpenAlexW2266856284MaRDI QIDQ323195
Publication date: 7 October 2016
Published in: European Journal of Operational Research (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1602.01932
fixed pointproximal point algorithmHalpern algorithmKrasnosel'skiĭ-Mann algorithmincremental subgradient method
Convex programming (90C25) Derivative-free methods and methods using generalized derivatives (90C56) Fixed-point theorems (47H10) Programming in abstract spaces (90C48)
Related Items (8)
Two new self-adaptive algorithms for solving the split common null point problem with multiple output sets in Hilbert spaces ⋮ Almost sure convergence of random projected proximal and subgradient algorithms for distributed nonsmooth convex optimization ⋮ Two stochastic optimization algorithms for convex optimization with fixed point constraints ⋮ Fixed point quasiconvex subgradient method ⋮ A new iteration technique for nonlinear operators as concerns convex programming and feasibility problems ⋮ Decentralized hierarchical constrained convex optimization ⋮ Convergence of a distributed method for minimizing sum of convex functions with fixed point constraints ⋮ Iterative methods for parallel convex optimization with fixed point constraints
Uses Software
Cites Work
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- Parallel computing subgradient method for nonsmooth convex optimization over the intersection of fixed point sets of nonexpansive mappings
- Convergence analysis of iterative methods for nonsmooth convex optimization over fixed point sets of quasi-nonexpansive mappings
- Algorithms of common solutions for variational inclusions, mixed equilibrium problems and fixed point problems
- Iterative approximation of fixed points
- Projected subgradient techniques and viscosity methods for optimization with variational inequality constraints
- Optimal solutions for unrelated parallel machines scheduling problems using convex quadratic reformulations
- Approximation of fixed points of nonexpansive mappings
- Error stability properties of generalized gradient-type algorithms
- VI-constrained hemivariational inequalities: distributed algorithms and power control in ad-hoc networks
- A viscosity method with no spectral radius requirements for the split common fixed point problem
- A theorem on maximal monotonic sets in Hilbert space
- Approximate methods for convex minimization problems with series-parallel structure
- Hard-constrained inconsistent signal feasibility problems
- Incremental Subgradient Methods for Nondifferentiable Optimization
- A Class of Randomized Primal-Dual Algorithms for Distributed Optimization
- Incremental subgradient method for nonsmooth convex optimization with fixed point constraints
- Proximal Splitting Methods in Signal Processing
- Minimizing the Moreau Envelope of Nonsmooth Convex Functions over the Fixed Point Set of Certain Quasi-Nonexpansive Mappings
- Incremental Subgradients for Constrained Convex Optimization: A Unified Framework and New Methods
- Splitting Algorithms for the Sum of Two Nonlinear Operators
- Monotone Operators and the Proximal Point Algorithm
- Robust Wideband Beamforming by the Hybrid Steepest Descent Method
- Distributed Subgradient Methods for Multi-Agent Optimization
- On Distributed Averaging Algorithms and Quantization Effects
- Acceleration Method Combining Broadcast and Incremental Distributed Optimization Algorithms
- Fixed Point Optimization Algorithms for Distributed Optimization in Networked Systems
- A block-iterative surrogate constraint splitting method for quadratic signal recovery
- Fixed points of nonexpanding maps
- Weak convergence of the sequence of successive approximations for nonexpansive mappings
- Mean Value Methods in Iteration
- Convex analysis and monotone operator theory in Hilbert spaces
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