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A framework for applying subgradient methods

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A framework for applying subgradient methods
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24
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CC Attribution - NonCommercial - NoDerivatives 4.0 International:
You are free to use, copy, distribute and transmit the work or content in unchanged form for any legal and non-commercial purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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I discuss a framework that came to mind five years ago, in trying to solve an algorithmic problem in the context of hyperbolic programming. I never solved that problem, but the framework has proved to have interesting algorithmic consequences for convex optimization generally.