Riemannian smoothing gradient type algorithms for nonsmooth optimization problem on compact Riemannian submanifold embedded in Euclidean space
DOI10.1007/s00245-023-10061-xarXiv2212.03526MaRDI QIDQ6058520
Jiang Hu, Zheng Peng, Weihe Wu, Kangkang Deng
Publication date: 1 November 2023
Published in: Applied Mathematics and Optimization (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2212.03526
smoothing techniqueiteration complexityMoreau envelopenonconvex and nonsmooth optimizationRiemannian gradient methods
Large-scale problems in mathematical programming (90C06) Applications of mathematical programming (90C90) Nonconvex programming, global optimization (90C26) Nonlinear programming (90C30) Stochastic programming (90C15)
Cites Work
- Unnamed Item
- A new approach to the proximal point method: convergence on general Riemannian manifolds
- Adaptive smoothing algorithms for nonsmooth composite convex minimization
- Global convergence of ADMM in nonconvex nonsmooth optimization
- A first-order primal-dual algorithm for convex problems with applications to imaging
- Simple algorithms for optimization on Riemannian manifolds with constraints
- Stochastic approximation on Riemannian manifolds
- Variable smoothing for weakly convex composite functions
- Variable smoothing for convex optimization problems using stochastic gradients
- A brief introduction to manifold optimization
- A collection of nonsmooth Riemannian optimization problems
- Trust-region methods on Riemannian manifolds
- Robust Low-Rank Matrix Completion by Riemannian Optimization
- A smoothing stochastic gradient method for composite optimization
- A Riemannian Gradient Sampling Algorithm for Nonsmooth Optimization on Manifolds
- Adaptive Quadratically Regularized Newton Method for Riemannian Optimization
- Proximal Point Algorithm On Riemannian Manifolds
- A Riemannian BFGS Method Without Differentiated Retraction for Nonconvex Optimization Problems
- Line Search Algorithms for Locally Lipschitz Functions on Riemannian Manifolds
- Weakly Convex Optimization over Stiefel Manifold Using Riemannian Subgradient-Type Methods
- An Introduction to Optimization on Smooth Manifolds
- Continuation Methods for Riemannian Optimization
- Global rates of convergence for nonconvex optimization on manifolds
- Riemannian Optimization and Its Applications
- Compressed modes for variational problems in mathematics and physics
- Douglas--Rachford Splitting and ADMM for Nonconvex Optimization: Tight Convergence Results
- Proximal Gradient Method for Nonsmooth Optimization over the Stiefel Manifold
- Riemannian Stochastic Variance Reduced Gradient Algorithm with Retraction and Vector Transport
- Stochastic Gradient Descent on Riemannian Manifolds
- Spherical Mesh Adaptive Direct Search for Separating Quasi-Uncorrelated Sources by Range-Based Independent Component Analysis
- Range-Based ICA Using a Nonsmooth Quasi-Newton Optimizer for Electroencephalographic Source Localization in Focal Epilepsy
- The Gradient Projection Method Along Geodesics
- A manifold inexact augmented Lagrangian method for nonsmooth optimization on Riemannian submanifolds in Euclidean space
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