On the equivalence of inexact proximal ALM and ADMM for a class of convex composite programming
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Publication:2220656
DOI10.1007/s10107-019-01423-xzbMath1458.90509arXiv1803.10803OpenAlexW2971348295WikidataQ127331854 ScholiaQ127331854MaRDI QIDQ2220656
Liang Chen, Xudong Li, Kim-Chuan Toh, Defeng Sun
Publication date: 25 January 2021
Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1803.10803
augmented Lagrangian methodalternating direction method of multiplierssymmetric Gauss-Seidel decompositionproximal term
Numerical mathematical programming methods (65K05) Convex programming (90C25) Large-scale problems in mathematical programming (90C06) Quadratic programming (90C20) Decomposition methods (49M27)
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Cites Work
- Unnamed Item
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- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Fast Algorithms for Large-Scale Generalized Distance Weighted Discrimination
- A rank-corrected procedure for matrix completion with fixed basis coefficients
- SDPNAL+: a majorized semismooth Newton-CG augmented Lagrangian method for semidefinite programming with nonnegative constraints
- An efficient inexact symmetric Gauss-Seidel based majorized ADMM for high-dimensional convex composite conic programming
- A note on the convergence of ADMM for linearly constrained convex optimization problems
- A boundary point method to solve semidefinite programs
- An inexact primal-dual path following algorithm for convex quadratic SDP
- Lectures on numerical methods for non-linear variational problems
- A dual algorithm for the solution of nonlinear variational problems via finite element approximation
- QSDPNAL: a two-phase augmented Lagrangian method for convex quadratic semidefinite programming
- Semidefinite programming approach for the quadratic assignment problem with a sparse graph
- Convex optimization learning of faithful Euclidean distance representations in nonlinear dimensionality reduction
- Spectral operators of matrices
- A block symmetric Gauss-Seidel decomposition theorem for convex composite quadratic programming and its applications
- Noisy low-rank matrix completion with general sampling distribution
- Multiplier and gradient methods
- Atomic Decomposition by Basis Pursuit
- A Majorized ADMM with Indefinite Proximal Terms for Linearly Constrained Convex Composite Optimization
- Hankel Matrix Rank Minimization with Applications to System Identification and Realization
- Regularization Methods for SDP Relaxations in Large-Scale Polynomial Optimization
- Semidefinite Relaxations for Best Rank-1 Tensor Approximations
- A Newton-CG Augmented Lagrangian Method for Semidefinite Programming
- An Adaptive Correction Approach for Tensor Completion
- Penalized and Constrained Optimization: An Application to High-Dimensional Website Advertising
- Algorithms for Fitting the Constrained Lasso
- Optimization and nonsmooth analysis
- Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming
- Practical Aspects of the Moreau--Yosida Regularization: Theoretical Preliminaries
- Consensus in Ad Hoc WSNs With Noisy Links—Part I: Distributed Estimation of Deterministic Signals
- Distributed Sparse Linear Regression
- Another Look at Distance-Weighted Discrimination
- Solving Large Scale Semidefinite Programs via an Iterative Solver on the Augmented Systems
- Frequency planning and ramifications of coloring
- Weighted Complementarity Problems---A New Paradigm for Computing Equilibria
- A linearly convergent majorized ADMM with indefinite proximal terms for convex composite programming and its applications
- Regularization Methods for Semidefinite Programming
- Linear Rate Convergence of the Alternating Direction Method of Multipliers for Convex Composite Programming
- A Convergent 3-Block SemiProximal Alternating Direction Method of Multipliers for Conic Programming with 4-Type Constraints
- Restricted strong convexity and weighted matrix completion: Optimal bounds with noise
- Implicit Functions and Solution Mappings
- Approximating K‐means‐type Clustering via Semidefinite Programming
- Robust Estimation of a Location Parameter
- Convex Analysis
- A Schur complement based semi-proximal ADMM for convex quadratic conic programming and extensions