The gradient projection method with Armijo's step size on manifolds
From MaRDI portal
Publication:2059547
DOI10.1134/S0965542521110038zbMath1481.65087OpenAlexW4200492738MaRDI QIDQ2059547
R. A. Kamalov, Maxim V. Balashov
Publication date: 14 December 2021
Published in: Computational Mathematics and Mathematical Physics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1134/s0965542521110038
gradient projection methodmatrix manifoldsproximal smoothnessArmijo step sizenonconvex optimization problem
Numerical mathematical programming methods (65K05) Nonconvex programming, global optimization (90C26)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Introductory lectures on convex optimization. A basic course.
- The gradient projection algorithm for smooth sets and functions in nonconvex case
- Gradient projection method on matrix manifolds
- Quadratic optimization with orthogonality constraint: explicit Łojasiewicz exponent and linear convergence of retraction-based line-search and stochastic variance-reduced gradient methods
- Convergence to equilibrium for discretizations of gradient-like flows on Riemannian manifolds
- Minimizing a Quadratic Over a Sphere
- Projection-like Retractions on Matrix Manifolds
- Convergence Results for Projected Line-Search Methods on Varieties of Low-Rank Matrices Via Łojasiewicz Inequality
- Strong and Weak Convexity of Sets and Functions
- The Geometry of Algorithms with Orthogonality Constraints
- Nonmonotone Spectral Projected Gradient Methods on Convex Sets
- Packing Lines, Planes, etc.: Packings in Grassmannian Spaces
- Gradient Projection and Conditional Gradient Methods for Constrained Nonconvex Minimization
- Convex programming in Hilbert space
- The Gradient Projection Method Along Geodesics
This page was built for publication: The gradient projection method with Armijo's step size on manifolds