A Unified Primal-Dual Algorithm Framework for Inequality Constrained Problems
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computational Theory and Mathematics,General Engineering,Theoretical Computer Science,Software,Applied Mathematics,Computational Mathematics,Numerical Analysis
Link
https://link.springer.com/content/pdf/10.1007/s10915-023-02346-8.pdf
Reference38 articles.
1. Bauschke, H.H., Combettes, P.L., et al.: Convex Analysis and Monotone Operator Theory in Hilbert Spaces, vol. 408. Springer, New York (2011)
2. Bertsekas, D.: Convex Optimization Algorithms. Athena Scientific, Nashua (2015)
3. Cai, X., Han, D., Yuan, X.: On the convergence of the direct extension of ADMM for three-block separable convex minimization models with one strongly convex function. Comput. Optim. Appl. 66(1), 39–73 (2017)
4. Chambolle, A., Pock, T.: A first-order primal-dual algorithm for convex problems with applications to imaging. J. Math. Imaging Vis. 40(1), 120–145 (2011)
5. Chambolle, A., Pock, T.: On the ergodic convergence rates of a first-order primal-dual algorithm. Math. Program. 159(1), 253–287 (2016)
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