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Accelerated Proximal Point Method and Forward Method for Monotone Inclusions
| Content Provider | Semantic Scholar |
|---|---|
| Author | Kim, Dong-Hwan |
| Copyright Year | 2019 |
| Abstract | This paper proposes an accelerated proximal point method for maximally monotone operators. The proof is computer-assisted via the performance estimation problem approach. The proximal point method includes various well-known convex optimization methods, such as the proximal method of multipliers and the alternating direction method of multipliers, and thus the proposed acceleration has wide applications. Numerical experiments are presented to demonstrate the accelerating behaviors. In addition, this paper shows that the proposed acceleration applies to the forward method for cocoercive operators. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://arxiv-export-lb.library.cornell.edu/pdf/1905.05149 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |