A Field Guide to Forward-Backward Splitting with a FASTA Implementation
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| Authors | Tom Goldstein, Christoph Studer, Richard G. Baraniuk |
| Journal/Conference Name | ArXiv |
| Paper Category | Other |
| Paper Abstract | Non-differentiable and constrained optimization play a key role in machine learning, signal and image processing, communications, and beyond. For high-dimensional minimization problems involving large datasets or many unknowns, the forward-backward splitting method provides a simple, practical solver. Despite its apparently simplicity, the performance of the forward-backward splitting is highly sensitive to implementation details. |
| Date of publication | 2014 |
| Code Programming Language | R |
| Comment |
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