On the Convergence of Bregman ADMM With Variational Inequality

On the Convergence of Bregman ADMM With Variational Inequality

The alternating direction method of multipliers (ADMM) is one of most foundational algorithms for linear constrained composite minimization problems. For different specific problems, variations of ADMM (like linearized ADMM, proximal ADMM) are developed. By using the Bregman distances, lots of ADMMs...

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Bibliographic Details
Main Authors: Peibing Du, Hao Jiang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Convex proximal inertial gradient descent
heavy-ball method
non-ergodic convergence rates
block coordinate descent
computational complexity
machine learning algorithms
Online Access:https://ieeexplore.ieee.org/document/8990114/

Internet

https://ieeexplore.ieee.org/document/8990114/

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