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The effect of perturbations on the convergence rates of optimization algorithms
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/bf01460129openalex-snapshot
Extremal types for certainL p minimization problems and associated large scale nonlinear programs
inferredcites →https://doi.org/10.1016/0041-5553(66)90114-5openalex-snapshot
Constrained minimization methods
inferredcites →https://doi.org/10.1090/s0025-5718-1969-0247746-7openalex-snapshot
On the Approximate Minimization of Functionals
inferredcites →https://doi.org/10.1109/tac.1976.1101194openalex-snapshot
On the Goldstein-Levitin-Polyak gradient projection method
inferredcites →https://doi.org/10.1137/0317015openalex-snapshot
Rates of Convergence for Conditional Gradient Algorithms Near Singular and Nonsingular Extremals
inferredcites →https://doi.org/10.1137/0318035openalex-snapshot
Convergence Rates for Conditional Gradient Sequences Generated by Implicit Step Length Rules
inferredcites →https://doi.org/10.1137/0319022openalex-snapshot
Global and Asymptotic Convergence Rate Estimates for a Class of Projected Gradient Processes
inferredcites →https://doi.org/10.2307/2005894openalex-snapshot
The Approximate Minimization of Functionals
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/0-387-24255-4_20openalex-snapshot
On a Quasi-Consistent Approximations Approach to Optimization Problems with Two Numerical Precision Parameters
inferred← citeshttps://doi.org/10.1007/978-1-4613-3632-7_6openalex-snapshot
Gradient-Related Constrained Minimization Algorithms in Function Spaces: Convergence Properties and Computational Implications
inferred← citeshttps://doi.org/10.1007/978-3-662-02851-3_10openalex-snapshot
Topics in Modern Computational Methods for Optimal Control Problems
inferred← citeshttps://doi.org/10.1007/bf00938596openalex-snapshot
Rates of convergence for adaptive Newton methods
inferred← citeshttps://doi.org/10.1007/bf01442181openalex-snapshot
Newton's method for singular constrained optimization problems
inferred← citeshttps://doi.org/10.1007/bf01449042openalex-snapshot
Newton?Goldstein convergence rates for convex constrained minimization problems with singular solutions
inferred← citeshttps://doi.org/10.1007/bf02055200openalex-snapshot
Convergence of algorithms for perturbed optimization problems
inferred← citeshttps://doi.org/10.1016/b978-0-08-037036-1.50035-5openalex-snapshot
THE ROLE OF GROWTH RATES FOR GAUSS–NEWTON METHODS AND PARAMETER IDENTIFICATION PROBLEMS
inferred← citeshttps://doi.org/10.1016/s1474-6670(17)53539-9openalex-snapshot
The Role of Growth Rates for Gauss-Newton Methods and Parameter Identification Problems
inferred← citeshttps://doi.org/10.1109/cdc.1986.267278openalex-snapshot
Quasi Newton methods and unconstrained optimal control problems
inferred← citeshttps://doi.org/10.1137/0324071openalex-snapshot
Diagonally Modified Conditional Gradient Methods for Input Constrained Optimal Control Problems
inferred← citeshttps://doi.org/10.1137/0325083openalex-snapshot
Quasi-Newton Methods and Unconstrained Optimal Control Problems
inferred← citeshttps://doi.org/10.1137/0327002openalex-snapshot
Convergence of SQP-Like Methods for Constrained Optimization
inferred← citeshttps://doi.org/10.1137/0330072openalex-snapshot
Variants of the Kuhn–Tucker Sufficient Conditions in Cones of Nonnegative Functions
inferred← citeshttps://doi.org/10.1137/1.9781611970920openalex-snapshot
Iterative Methods for Optimization
inferred← citeshttps://doi.org/10.1137/s0363012900369599openalex-snapshot
Consistent Approximations and Approximate Functions and Gradients in Optimal Control
inferred← citeshttps://doi.org/10.1137/s0363012989174110openalex-snapshot
On the Optimal Control of Systems Described by Evolution Equations
inferred← citeshttps://doi.org/10.1137/s0363012992233652openalex-snapshot
On the Gradient Projection Method for Optimal Control Problems with Nonnegative $\mathcal{L}^2 $ Inputs
inferred← citeshttps://doi.org/10.1137/s0363012994266127openalex-snapshot
On ${\text{L}}^2 $ Sufficient Conditions and the Gradient Projection Method for Optimal Control Problems
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