A note on approximate accelerated forward-backward methods with absolute and relative errors, and possibly strongly convex objectives
In this short note, we provide a simple version of an accelerated forward-backward method (a.k.a. Nesterov’s accelerated proximal gradient method) possibly relying on approximate proximal operators and allowing to exploit strong convexity of the objective function. The method supports both relative...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Université de Montpellier
2022-01-01
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| Series: | Open Journal of Mathematical Optimization |
| Online Access: | https://ojmo.centre-mersenne.org/articles/10.5802/ojmo.12/ |
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