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Tight Stationarity Transfer and Repeatability for Inexact Proximal-Gradient Methods
Proximal-gradient methods are widely used for composite optimization, but inexact proximal updates introduce a residual in the proximal optimality condition, complicating the analysis of how stationarity changes across a step. We study this question for composite objectives consisting of a smooth co
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