On the Information-Adaptive Variants of the ADMM: An Iteration Complexity Perspective

@article{Gao2018OnTI,
  title={On the Information-Adaptive Variants of the ADMM: An Iteration Complexity Perspective},
  author={Xiang Gao and Bo Jiang and Shuzhong Zhang},
  journal={J. Sci. Comput.},
  year={2018},
  volume={76},
  pages={327-363}
}
Designing algorithms for an optimization model often amounts to maintaining a balance between the degree of information to request from the model on the one hand, and the computational speed to expect on the other hand. Naturally, the more information is available, the faster one can expect the algorithm to converge. The popular algorithm of ADMM demands that objective function is easy to optimize once the coupled constraints are shifted to the objective with multipliers. However, in many… CONTINUE READING
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Random Gradient-Free Minimization of Convex Functions

Foundations of Computational Mathematics • 2017
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T. Lin, S. Ma, S. Zhang
Optimization Online, • 2014
View 3 Excerpts

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