Multi-block nonconvex nonsmooth proximal ADMM: convergence and rates under Kurdyka-Łojasiewicz property
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Publication:2231349
DOI10.1007/s10957-021-01919-7zbMath1478.90099arXiv2009.04014OpenAlexW3196456922MaRDI QIDQ2231349
Publication date: 29 September 2021
Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2009.04014
convergenceconvergence ratesnonconvex nonsmooth optimizationproximal ADMMKurdyka-Łojasiewicz property
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Cites Work
- Unnamed Item
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Nearly unbiased variable selection under minimax concave penalty
- On the convergence properties of a majorized alternating direction method of multipliers for linearly constrained convex optimization problems with coupled objective functions
- Iteration complexity analysis of multi-block ADMM for a family of convex minimization without strong convexity
- Fast alternating linearization methods for minimizing the sum of two convex functions
- Proximal alternating linearized minimization for nonconvex and nonsmooth problems
- A splitting method for orthogonality constrained problems
- GAITA: a Gauss-Seidel iterative thresholding algorithm for \(\ell_q\) regularized least squares regression
- On the linear convergence of the alternating direction method of multipliers
- On the sublinear convergence rate of multi-block ADMM
- On the convergence of the proximal algorithm for nonsmooth functions involving analytic features
- A dual algorithm for the solution of nonlinear variational problems via finite element approximation
- A proximal-based deomposition method for compositions method for convex minimization problems
- Global convergence of unmodified 3-block ADMM for a class of convex minimization problems
- Parallel multi-block ADMM with \(o(1/k)\) convergence
- Structured nonconvex and nonsmooth optimization: algorithms and iteration complexity analysis
- Global convergence of ADMM in nonconvex nonsmooth optimization
- Calculus of the exponent of Kurdyka-Łojasiewicz inequality and its applications to linear convergence of first-order methods
- A first-order primal-dual algorithm for convex problems with applications to imaging
- A note on the alternating direction method of multipliers
- Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward-backward splitting, and regularized Gauss-Seidel methods
- Bregman operator splitting with variable stepsize for total variation image reconstruction
- Efficient alternating minimization methods for variational edge-weighted colorization models
- On the convergence analysis of the alternating direction method of multipliers with three blocks
- Splitting methods with variable metric for Kurdyka-Łojasiewicz functions and general convergence rates
- On non-ergodic convergence rate of Douglas-Rachford alternating direction method of multipliers
- On the global and linear convergence of the generalized alternating direction method of multipliers
- An alternating direction approximate Newton algorithm for ill-conditioned inverse problems with application to parallel MRI
- Multiplier and gradient methods
- An $\mathcal O(1/{k})$ Convergence Rate for the Variable Stepsize Bregman Operator Splitting Algorithm
- Hankel Matrix Rank Minimization with Applications to System Identification and Realization
- On the $O(1/n)$ Convergence Rate of the Douglas–Rachford Alternating Direction Method
- Optimization with Sparsity-Inducing Penalties
- Alternating Direction Method with Gaussian Back Substitution for Separable Convex Programming
- Fast Multiple-Splitting Algorithms for Convex Optimization
- Convergence Analysis of Alternating Direction Method of Multipliers for a Family of Nonconvex Problems
- Alternating direction methods for classical and ptychographic phase retrieval
- Proximal Alternating Minimization and Projection Methods for Nonconvex Problems: An Approach Based on the Kurdyka-Łojasiewicz Inequality
- A Fast Relaxed Normal Two Split Method and an Effective Weighted TV Approach for Euler's Elastica Image Inpainting
- The Numerical Solution of Parabolic and Elliptic Differential Equations
- On the Numerical Solution of Heat Conduction Problems in Two and Three Space Variables
- Inertial Proximal ADMM for Linearly Constrained Separable Convex Optimization
- On Full Jacobian Decomposition of the Augmented Lagrangian Method for Separable Convex Programming
- Global Convergence of Splitting Methods for Nonconvex Composite Optimization
- Clarke Subgradients of Stratifiable Functions
- Characterizations of Łojasiewicz inequalities: Subgradient flows, talweg, convexity
- Variational Analysis
- <formula formulatype="inline"><tex Notation="TeX">$L_{1/2}$</tex> </formula> Regularization: Convergence of Iterative Half Thresholding Algorithm
- Parallel Algorithms for Constrained Tensor Factorization via Alternating Direction Method of Multipliers
- Convergence of alternating direction method for minimizing sum of two nonconvex functions with linear constraints
- Comments on «Wavelets in statistics: A review» by A. Antoniadis
- Fast Alternating Direction Optimization Methods
- Alternating Direction Method of Multipliers for a Class of Nonconvex and Nonsmooth Problems with Applications to Background/Foreground Extraction
- Regularization and Variable Selection Via the Elastic Net
- Convergence Rate Analysis of Several Splitting Schemes
- The Łojasiewicz Inequality for Nonsmooth Subanalytic Functions with Applications to Subgradient Dynamical Systems
- On the Global Linear Convergence of the ADMM with MultiBlock Variables
- Augmented Lagrangian alternating direction method for matrix separation based on low-rank factorization
- The direct extension of ADMM for multi-block convex minimization problems is not necessarily convergent
