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Long term dynamics of the subgradient method for Lipschitz path differentiable functions

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  • Bolte, Jérôme
  • Pauwels, Edouard
  • Rios-Zertuche, Rodolfo

Abstract

We consider the long-term dynamics of the vanishing stepsize subgradient method in the case when the objective function is neither smooth nor convex. We assume that this function is locally Lipschitz and path differentiable, i.e., admits a chain rule. Our study departs from other works in the sense that we focus on the behavior of the oscillations, and to do this we use closed measures. We recover known convergence results, establish new ones, and show a local principle of oscillation compensation for the velocities. Roughly speaking, the time average of gradients around one limit point vanishes. This allows us to further analyze the structure of oscillations, and establish their perpendicularity to the general drift.

Suggested Citation

  • Bolte, Jérôme & Pauwels, Edouard & Rios-Zertuche, Rodolfo, 2020. "Long term dynamics of the subgradient method for Lipschitz path differentiable functions," TSE Working Papers 20-1110, Toulouse School of Economics (TSE).
  • Handle: RePEc:tse:wpaper:124363
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    Cited by:

    1. Le, Tam & Bolte, Jérôme & Pauwels, Edouard, 2022. "Subgradient sampling for nonsmooth nonconvex minimization," TSE Working Papers 22-1310, Toulouse School of Economics (TSE).

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