Inexact gradient projection method with relative error tolerance
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Publication:2696906
DOI10.1007/s10589-022-00425-4OpenAlexW3121994267MaRDI QIDQ2696906
A. A. Aguiar, L. F. Prudente, Orizon P. Ferreira
Publication date: 17 April 2023
Published in: Computational Optimization and Applications (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2101.11146
Nonlinear programming (90C30) Newton-type methods (49M15) Nonsmooth analysis (49J52) Numerical computation of solutions to systems of equations (65H10) Mathematical programming (90Cxx)
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- On the convergence properties of the projected gradient method for convex optimization
- Convergence of a projected gradient method variant for quasiconvex objectives
- Dykstra's algorithm for constrained least-squares rectangular matrix problems
- Introductory lectures on convex optimization. A basic course.
- Newton's method with feasible inexact projections for solving constrained generalized equations
- Least-squares solution of \(F=PG\) over positive semidefinite symmetric \(P\)
- On the inexact scaled gradient projection method
- Convergence of the steepest descent method for minimizing quasiconvex functions
- A Krylov--Schur Algorithm for Large Eigenproblems
- Smoothing Functions for Second-Order-Cone Complementarity Problems
- A projected gradient method for optimization over density matrices
- Conditional Gradient Sliding for Convex Optimization
- Accelerated and Inexact Forward-Backward Algorithms
- Introduction to Nonlinear Optimization
- A Nonlinear Programming Problem in Statistics (Educational Testing)
- On the Goldstein-Levitin-Polyak gradient projection method
- Linear Matrix Inequalities in System and Control Theory
- ARPACK Users' Guide
- Inexact spectral projected gradient methods on convex sets
- Nonmonotone Spectral Projected Gradient Methods on Convex Sets
- On the Convergence of Inexact Projection Primal First-Order Methods for Convex Minimization
- Non-asymptotic convergence analysis of inexact gradient methods for machine learning without strong convexity
- Optimization Methods for Large-Scale Machine Learning
- Inexact Gradient Projection and Fast Data Driven Compressed Sensing
- Full convergence of the steepest descent method with inexact line searches
- A proximal regularization of the steepest descent method
- Projection-free accelerated method for convex optimization
- Inexact primal–dual gradient projection methods for nonlinear optimization on convex set
- Complexity of gradient descent for multiobjective optimization
- An Inexact Projected Gradient Method for Sparsity-Constrained Quadratic Measurements Regression
- On first-order algorithms forl1/nuclear norm minimization
- Convex programming in Hilbert space