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Proximal gradient methods are a generalized form of projection used to solve non-differentiable convex optimization problems.
Projection onto convex sets (POCS) & Overview
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proximal convex gradient displaystyle methods optimization projection operator method used problems algorithm non-differentiable algorithms operators form functions sets pocs see
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Proximal gradient method | related to Examples | Special | 0.60 | section |
| Proximal gradient method | related to Examples | Proximal Gradient Methods | 0.60 | section |
| Proximal gradient method | related to Examples | Projected LandweberAlternating | 0.60 | section |
| Proximal gradient method | related to External links | Stephen Boyd | 0.60 | section |
| Proximal gradient method | related to External links | Lieven Vandenberghe Book | 0.60 | section |
| Proximal gradient method | related to External links | Convex | 0.60 | section |
| Proximal gradient method | related to External links | Convex Optimization | 0.60 | section |
| Proximal gradient method | related to External links | EE364b | 0.60 | section |
| Proximal gradient method | related to External links | Convex Optimization II | 0.60 | section |
| Proximal gradient method | related to External links | Stanford | 0.60 | section |
| Proximal gradient method | related to External links | Lieven Vandenberghe Notes Lecture | 0.60 | section |
| Proximal gradient method | related to External links | Julia | 0.60 | section |
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