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Error bounds and convergence analysis of feasible descent methods: a general approach

https://doi.org/10.1007/bf02096261
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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A quadratic programming procedure
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A convex programming procedure
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Linear and Nonlinear Programming
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Necessary and sufficient conditions for the convergence of iterative methods for the linear complementarity problem
inferredcites →https://doi.org/10.1007/bf00934765openalex-snapshot
On the convergence of a basic iterative method for the implicit complementarity problem
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On the gradient-projection method for solving the nonsymmetric linear complementarity problem
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On the convergence of projected gradient processes to singular critical points
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More results on the convergence of iterative methods for the symmetric linear complementarity problem
inferredcites →https://doi.org/10.1007/bf00939948openalex-snapshot
On the convergence of the coordinate descent method for convex differentiable minimization
inferredcites →https://doi.org/10.1007/bf01268170openalex-snapshot
Solution of symmetric linear complementarity problems by iterative methods
inferredcites →https://doi.org/10.1007/bf01448356openalex-snapshot
Error bounds for strongly convex programs and (super)linearly convergent iterative schemes for the least 2-norm solution of linear programs
inferredcites →https://doi.org/10.1007/bf01448362openalex-snapshot
Variable metric gradient projection processes in convex feasible sets defined by nonlinear inequalities
inferredcites →https://doi.org/10.1007/bf01580851openalex-snapshot
On the convergence properties of Hildreth's quadratic programming algorithm
inferredcites →https://doi.org/10.1007/bf01582267openalex-snapshot
Error bounds for nondegenerate monotone linear complementarity problems
inferredcites →https://doi.org/10.1007/bf02591989openalex-snapshot
Inexact Newton methods for the nonlinear complementarity problem
inferredcites →https://doi.org/10.1007/bf02591991openalex-snapshot
Error bounds for monotone linear complementarity problems
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Some continuity properties of polyhedral multifunctions
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Projection methods for variational inequalities with application to the traffic assignment problem
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Generalized equations and their solutions, part II: Applications to nonlinear programming
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Error bounds for the linear complementarity problem with a P-matrix
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Global error bounds for monotone affine variational inequality problems
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Constrained minimization methods
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The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming
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On a global error bound for a class of monotone affine variational inequality problems
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Sparsity-preserving sor algorithms for separable quadratic and linear programming
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Linear and nonlinear programming.
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Application Of Khobotov’s Algorithm To Variational Inequalities And Network Equilibrium Problems
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Convex programming in Hilbert space
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Gradient projection techniques for large-scale optimization problems
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On the Goldstein-Levitin-Polyak gradient projection method
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Distributed asynchronous optimal routing in data networks
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Distributed asynchronous deterministic and stochastic gradient optimization algorithms
inferredcites →https://doi.org/10.1137/0111043openalex-snapshot
Minimizing Certain Convex Functions
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The Solution of a Quadratic Programming Problem Using Systematic Overrelaxation
inferredcites →https://doi.org/10.1137/0314020openalex-snapshot
Combined Primal–Dual and Penalty Methods for Convex Programming
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Monotone Operators and the Proximal Point Algorithm
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Global and Asymptotic Convergence Rate Estimates for a Class of Projected Gradient Processes
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Projected Newton Methods for Optimization Problems with Simple Constraints
inferredcites →https://doi.org/10.1137/0322061openalex-snapshot
Two-Metric Projection Methods for Constrained Optimization
inferredcites →https://doi.org/10.1137/0325023openalex-snapshot
Iterative Methods for Large Convex Quadratic Programs: A Survey
inferredcites →https://doi.org/10.1137/0328011openalex-snapshot
Dual Ascent Methods for Problems with Strictly Convex Costs and Linear Constraints: A Unified Approach
inferredcites →https://doi.org/10.1137/0329022openalex-snapshot
On the Convergence of the Proximal Point Algorithm for Convex Minimization
inferredcites →https://doi.org/10.1137/0329057openalex-snapshot
On the Convergence of a Matrix Splitting Algorithm for the Symmetric Monotone Linear Complementarity Problem
inferredcites →https://doi.org/10.1137/0329062openalex-snapshot
A Subspace Decomposition Principle for Scaled Gradient Projection Methods: Global Theory
inferredcites →https://doi.org/10.1137/0330025openalex-snapshot
On the Linear Convergence of Descent Methods for Convex Essentially Smooth Minimization
inferredcites →https://doi.org/10.1137/0702022openalex-snapshot
On the Solution of Singular and Semidefinite Linear Systems by Iteration
inferredcites →https://doi.org/10.1137/0801009openalex-snapshot
Convergence of Iterates of an Inexact Matrix Splitting Algorithm for the Symmetric Monotone Linear Complementarity Problem
inferredcites →https://doi.org/10.1137/0801025openalex-snapshot
On Dual Convergence and the Rate of Primal Convergence of Bregman’s Convex Programming Method
inferredcites →https://doi.org/10.1137/0801036openalex-snapshot
On the Rate of Convergence of a Partially Asynchronous Gradient Projection Algorithm
inferredcites →https://doi.org/10.1137/0802004openalex-snapshot
Error Bound and Convergence Analysis of Matrix Splitting Algorithms for the Affine Variational Inequality Problem
inferredcites →https://doi.org/10.1137/0803003openalex-snapshot
Error Bound and Reduced-Gradient Projection Algorithms for Convex Minimization over a Polyhedral Set
inferredcites →https://doi.org/10.1137/0803008openalex-snapshot
Remarks on Convergence of the Matrix Splitting Algorithm for the Symmetric Linear Complementarity Problem
inferredcites →https://doi.org/10.1137/1.9780898719468openalex-snapshot
Iterative Solution of Nonlinear Equations in Several Variables
inferredcites →https://doi.org/10.1287/moor.1.2.97openalex-snapshot
Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming
inferredcites →https://doi.org/10.1287/moor.12.3.474openalex-snapshot
A Posteriori Error Bounds for the Linearly-Constrained Variational Inequality Problem
inferredcites →https://doi.org/10.1287/moor.18.4.846openalex-snapshot
On the Convergence Rate of Dual Ascent Methods for Linearly Constrained Convex Minimization
inferredcites →https://doi.org/10.2307/2004942openalex-snapshot
Iterative Solution of Nonlinear Equations in Several Variables
inferredcites →https://doi.org/10.6028/jres.049.027openalex-snapshot
On approximate solutions of systems of linear inequalities

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Weak Convexity and Approximate Subdifferentials
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Tight Error Bounds for Log-Determinant Cones Without Constraint Qualifications
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On growth error bound conditions with an application to heavy ball method
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Revisit Iterative Complexity of Some Projection-type Methods for Monotone Linear Variational Inequality Problems
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On Stochastic Mirror-prox Algorithms for Stochastic Cartesian Variational Inequalities: Randomized Block Coordinate and Optimal Averaging Schemes
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Perturbation Techniques for Convergence Analysis of Proximal Gradient Method and Other First-Order Algorithms via Variational Analysis
inferred← citeshttps://doi.org/10.1007/s11228-021-00591-3openalex-snapshot
Variational Analysis Perspective on Linear Convergence of Some First Order Methods for Nonsmooth Convex Optimization Problems
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Calm Local Optimality for Nonconvex-Nonconcave Minimax Problems
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A linearly convergent stochastic recursive gradient method for convex optimization
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On the rate of convergence of alternating minimization for non-smooth non-strongly convex optimization in Banach spaces
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QPALM: a proximal augmented lagrangian method for nonconvex quadratic programs
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On the Linear Convergence of the Approximate Proximal Splitting Method for Non-smooth Convex Optimization
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A Parallel Line Search Subspace Correction Method for Composite Convex Optimization
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Local Linear Convergence of an ADMM-Type Splitting Framework for Equality Constrained Optimization
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Augmented Lagrangian Methods for Convex Matrix Optimization Problems
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A Survey on Some Recent Developments of Alternating Direction Method of Multipliers
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A Survey on Some Recent Advances in Linear and Nonlinear Second-Order Cone Programming
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On linear convergence of iterative methods for the variational inequality problem
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Gradient descent-type methods
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Global Lipschitzian error bounds for semidefinite complementarity problems with emphasis on NCPs
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On the solution of convex QPQC problems with elliptic and other separable constraints with strong curvature
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Error bounds for non-polyhedral convex optimization and applications to linear convergence of FDM and PGM
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An inexact Newton-like conditional gradient method for constrained nonlinear systems
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An inexact quasi-Newton algorithm for large-scale ℓ1 optimization with box constraints
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Distributed optimization for degenerate loss functions arising from over-parameterization
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A global piecewise smooth Newton method for fast large-scale model predictive control
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Non-convex composite federated learning with heterogeneous data
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Asynchronous block coordinate gradient method with the communication noise
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Robust adaptive beamforming against large steering vector mismatch based on minimum dispersion
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Newton-MR: Inexact Newton Method with minimum residual sub-problem solver
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Nonmonotone gradient methods for vector optimization with a portfolio optimization application
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Scaling up Bayesian variational inference using distributed computing clusters
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Nonparallel hyperplane support vector machine for binary classification problems
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A proximal gradient descent method for the extended second-order cone linear complementarity problem
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Over relaxed hybrid proximal extragradient algorithm and its application to several operator splitting methods
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On convergence rate of the randomized Gauss-Seidel method
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ε-Proximal support vector machine for binary classification and its application in vehicle recognition
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Twin extreme learning machines for pattern classification
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Laplacian twin extreme learning machine for semi-supervised classification
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A coordinate descent margin based-twin support vector machine for classification
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Gap functions and global error bounds for differential variational–hemivariational inequalities
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Rate of convergence analysis of dual-based variables decomposition methods for strongly convex problems
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The adventures of a simple algorithm
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Some developments in general variational inequalities
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Some recent advances in projection-type methods for variational inequalities
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On Theory and Practice of Row Relaxation Methods
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First-Order Methods
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Tensor models: solution methods and applications
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Optimization algorithms for big data with application in wireless networks
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A Logarithmic-Quadratic Proximal Method for Variational Inequalities
inferred← citeshttps://doi.org/10.1023/a:1013048729944openalex-snapshot
Modified Goldstein–Levitin–Polyak Projection Method for Asymmetric Strongly Monotone Variational Inequalities
inferred← citeshttps://doi.org/10.1023/a:1017501703105openalex-snapshot
Convergence of a Block Coordinate Descent Method for Nondifferentiable Minimization
inferred← citeshttps://doi.org/10.1023/a:1018358602892openalex-snapshot
Decomposition Methods for Differentiable Optimization Problems over Cartesian Product Sets
inferred← citeshttps://doi.org/10.1023/a:1019637315803openalex-snapshot
Local Convergence Analysis of Projection-Type Algorithms: Unified Approach
inferred← citeshttps://doi.org/10.1023/a:1022602123316openalex-snapshot
Convergence Analysis of Perturbed Feasible Descent Methods
inferred← citeshttps://doi.org/10.1023/b:coap.0000049888.80264.25openalex-snapshot
Minimizing Quadratic Functions Subject to Bound Constraints with the Rate of Convergence and Finite Termination
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An inexact proximal decomposition method for variational inequalities with separable structure
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On the convergence of exact distributed generalisation and acceleration algorithm for convex optimisation
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Characterizations of local upper Lipschitz property of perturbed solutions to nonlinear second-order cone programs
inferred← citeshttps://doi.org/10.1080/02331934.2022.2154606openalex-snapshot
Convergence rate of the relaxed CQ algorithm under Hölderian type error bound property
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Accelerated overrelaxation algorithm for optimizing twin random vector functional link regression
inferred← citeshttps://doi.org/10.1080/02331934.2026.2663349openalex-snapshot
Complexity of inexact proximal point algorithm for minimizing convex functions with Holderian growth
inferred← citeshttps://doi.org/10.1080/02331934.2026.2672525openalex-snapshot
The convexity zoo: a taxonomy of function classes in optimization
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Multiobjective abstract schemas for descent algorithms: solving conflicts of objectives via a variational rationality perspective
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An inexact proximal Newton algorithm with partial Hessian information for nonsmooth separable optimization
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How much efficiency improvement can a spatiotemporal window generate for shared mobility? A case study in New York City
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Non-asymptotic convergence analysis of inexact gradient methods for machine learning without strong convexity
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A quasi-Newton modified LP-Newton method
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A stochastic approximation method for convex programming with many semidefinite constraints
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Convergence rate analysis of the gradient descent–ascent method for convex–concave saddle-point problems
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Globally convergent block-coordinate techniques for unconstrained optimization
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Tensor Canonical Correlation Analysis With Convergence and Statistical Guarantees
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Accelerated perturbation-resilient block-iterative projection methods with application to image reconstruction
inferred← citeshttps://doi.org/10.1088/1361-6420/ad3c67openalex-snapshot
A novel variational approach for multiphoton microscopy image restoration: from PSF estimation to 3D deconvolution
inferred← citeshttps://doi.org/10.1088/1361-6420/ae5aceopenalex-snapshot
Well-posedness and efficient algorithms for inverse optimal transport with bregman regularization
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Convergence rate analysis of an asynchronous space decomposition method for convex Minimization
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Randomized sketch descent methods for non-separable linearly constrained optimization
inferred← citeshttps://doi.org/10.1093/imanum/drad031openalex-snapshot
Convergence rate of inertial forward–backward algorithms based on the local error bound condition
inferred← citeshttps://doi.org/10.1093/imanum/dry040openalex-snapshot
Random permutations fix a worst case for cyclic coordinate descent
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The nonsmooth landscape of phase retrieval
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Statistical ranking with dynamic covariates
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Additive-Effect Assisted Learning
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Agnostic Process Tomography
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Successive overrelaxation for support vector machines
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Parallel and distributed random coordinate descent method for convex error bound minimization
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Global linear convergence in operator splitting methods
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Variance Amplification of Accelerated First-Order Algorithms for Strongly Convex Quadratic Optimization Problems
inferred← citeshttps://doi.org/10.1109/cdc40024.2019.9029983openalex-snapshot
Gradient Based Restart FISTA
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On Robustness of the Normalized Random Block Coordinate Method for Non-Convex Optimization
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Performance of Noisy Three-Step Accelerated First-Order Optimization Algorithms for Strongly Convex Quadratic Problems
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A Matrix Splitting Method for Composite Function Minimization
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ApproxIt: An approximate computing framework for iterative methods
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