Proximal gradient algorithm with trust region scheme on Riemannian manifold
From MaRDI portal
Publication:6123562
DOI10.1007/s10898-023-01326-4MaRDI QIDQ6123562
Yuanguo Zhu, Tao Yan, Shimin Zhao
Publication date: 5 April 2024
Published in: Journal of Global Optimization (Search for Journal in Brave)
Stiefel manifoldRiemannian optimizationtrust region methodsnonmonotoneoblique manifoldRiemannian proximal gradient method
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Accelerated gradient methods for nonconvex nonlinear and stochastic programming
- \(\varepsilon\)-subgradient algorithms for locally Lipschitz functions on Riemannian manifolds
- Generalized gradients and characterization of epi-Lipschitz sets in Riemannian manifolds
- An accelerated nonmonotone trust region method with adaptive trust region for unconstrained optimization
- Nonmonotonic trust region algorithm
- Nonmonotone trust region method for solving optimization problems
- Riemannian proximal gradient methods
- A brief introduction to manifold optimization
- A Riemannian symmetric rank-one trust-region method
- Iteration-complexity of gradient, subgradient and proximal point methods on Riemannian manifolds
- Trust-region methods on Riemannian manifolds
- A nonmonotone trust region method based on nonincreasing technique of weighted average of the successive function values
- Optimization theory and methods. Nonlinear programming
- Weakly Correlated Sparse Components with Nearly Orthonormal Loadings
- Optimization Methods on Riemannian Manifolds and Their Application to Shape Space
- A Riemannian BFGS Method for Nonconvex Optimization Problems
- On the Evaluation Complexity of Composite Function Minimization with Applications to Nonconvex Nonlinear Programming
- Proximal Point Algorithm On Riemannian Manifolds
- First-Order Methods in Optimization
- A Riemannian BFGS Method Without Differentiated Retraction for Nonconvex Optimization Problems
- A Nonmonotone Line Search Technique and Its Application to Unconstrained Optimization
- Nonsmooth trust region algorithms for locally Lipschitz functions on Riemannian manifolds
- An extension of fast iterative shrinkage‐thresholding algorithm to Riemannian optimization for sparse principal component analysis
- A Proximal Quasi-Newton Trust-Region Method for Nonsmooth Regularized Optimization
- Compressed modes for variational problems in mathematics and physics
- Proximal Gradient Method for Nonsmooth Optimization over the Stiefel Manifold
- A new, globally convergent Riemannian conjugate gradient method
- A Trust-region Method for Nonsmooth Nonconvex Optimization
This page was built for publication: Proximal gradient algorithm with trust region scheme on Riemannian manifold