Majorized iPADMM for Nonseparable Convex Minimization Models with Quadratic Coupling Terms
From MaRDI portal
Publication:6053487
DOI10.1142/s0217595922400024OpenAlexW4200611640MaRDI QIDQ6053487
Yumin Ma, Ting Li, Xing-Ju Cai, Yong-Zhong Song
Publication date: 19 October 2023
Published in: Asia-Pacific Journal of Operational Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1142/s0217595922400024
convergencenonseparable convex minimization modelquadratic coupling termsindefinite proximal termsmajorized iPADMM
Related Items
Cites Work
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- On the convergence properties of a majorized alternating direction method of multipliers for linearly constrained convex optimization problems with coupled objective functions
- Noisy matrix decomposition via convex relaxation: optimal rates in high dimensions
- Generalized ADMM with optimal indefinite proximal term for linearly constrained convex optimization
- Convergence study of indefinite proximal ADMM with a relaxation factor
- A dual algorithm for the solution of nonlinear variational problems via finite element approximation
- Parallel multi-block ADMM with \(o(1/k)\) convergence
- First-order algorithms for convex optimization with nonseparable objective and coupled constraints
- Extended ADMM and BCD for nonseparable convex minimization models with quadratic coupling terms: convergence analysis and insights
- Convergence study on strictly contractive peaceman-Rachford splitting method for nonseparable convex minimization models with quadratic coupling terms
- Optimization problems for machine learning: a survey
- Convergence analysis of positive-indefinite proximal ADMM with a Glowinski's relaxation factor
- On the equivalence of inexact proximal ALM and ADMM for a class of convex composite programming
- Optimally linearizing the alternating direction method of multipliers for convex programming
- A proximal alternating direction method for multi-block coupled convex optimization
- On the global and linear convergence of the generalized alternating direction method of multipliers
- A Majorized ADMM with Indefinite Proximal Terms for Linearly Constrained Convex Composite Optimization
- Splitting Methods in Communication, Imaging, Science, and Engineering
- Hankel Matrix Rank Minimization with Applications to System Identification and Realization
- Distributed Optimization With Local Domains: Applications in MPC and Network Flows
- A Block Successive Upper-Bound Minimization Method of Multipliers for Linearly Constrained Convex Optimization
- MIMO Cognitive Radio: A Game Theoretical Approach
- A linearly convergent majorized ADMM with indefinite proximal terms for convex composite programming and its applications
- On Alternating Direction Methods of Multipliers: A Historical Perspective
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
