Two-step inertial Bregman alternating minimization algorithm for nonconvex and nonsmooth problems
DOI10.1007/s10898-022-01176-6OpenAlexW4281387205MaRDI QIDQ2089886
Qiao-Li Dong, Jing Zhao, Feng Hui Wang, Michael Th. Rassias
Publication date: 24 October 2022
Published in: Journal of Global Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10898-022-01176-6
nonconvex optimizationBregman distanceKurdyka-Łojasiewicz inequalityalternating minimizationinertial algorithm
Nonconvex programming, global optimization (90C26) Nonlinear programming (90C30) Numerical optimization and variational techniques (65K10) Nonsmooth analysis (49J52) Nonlinear ill-posed problems (47J06)
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- Douglas-Rachford splitting for nonconvex optimization with application to nonconvex feasibility problems
- An inertial Tseng's type proximal algorithm for nonsmooth and nonconvex optimization problems
- Proximal alternating linearized minimization for nonconvex and nonsmooth problems
- Projected subgradient methods with non-Euclidean distances for non-differentiable convex minimization and variational inequalities
- On gradients of functions definable in o-minimal structures
- A proximal difference-of-convex algorithm with extrapolation
- Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward-backward splitting, and regularized Gauss-Seidel methods
- A new globally convergent algorithm for non-Lipschitz \(\ell_{p}-\ell_q\) minimization
- New Bregman projection methods for solving pseudo-monotone variational inequality problem
- Convergence analysis of the generalized splitting methods for a class of nonconvex optimization problems
- A Gauss-Seidel type inertial proximal alternating linearized minimization for a class of nonconvex optimization problems
- On linear convergence of non-Euclidean gradient methods without strong convexity and Lipschitz gradient continuity
- Inertial proximal alternating minimization for nonconvex and nonsmooth problems
- A Block Coordinate Descent Method for Regularized Multiconvex Optimization with Applications to Nonnegative Tensor Factorization and Completion
- iPiano: Inertial Proximal Algorithm for Nonconvex Optimization
- Convergence Analysis of Alternating Direction Method of Multipliers for a Family of Nonconvex Problems
- Outlier-Robust PCA: The High-Dimensional Case
- Proximal Alternating Minimization and Projection Methods for Nonconvex Problems: An Approach Based on the Kurdyka-Łojasiewicz Inequality
- Inertial Proximal Alternating Linearized Minimization (iPALM) for Nonconvex and Nonsmooth Problems
- Global Convergence of Splitting Methods for Nonconvex Composite Optimization
- Variational Analysis
- Regularizing with Bregman--Moreau Envelopes
- First Order Methods Beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems
- A Symmetric Alternating Direction Method of Multipliers for Separable Nonconvex Minimization Problems
- A Non-Euclidean Gradient Descent Framework for Non-Convex Matrix Factorization
- Acceleration and Global Convergence of a First-Order Primal-Dual Method for Nonconvex Problems
- Modified extragradient method with Bregman distance for variational inequalities
- The Łojasiewicz Inequality for Nonsmooth Subanalytic Functions with Applications to Subgradient Dynamical Systems
- Interior Gradient and Proximal Methods for Convex and Conic Optimization
- Signal Recovery by Proximal Forward-Backward Splitting
- Some methods of speeding up the convergence of iteration methods
- Functional Operators (AM-22), Volume 2
- Compressed sensing
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