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The structure of conservative gradient fields

arXiv 2101.00699 ↗First posted 3 Jan 2021math.OC cs.LG cs.NAcited by 4

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Abstract (arXiv)

The classical Clarke subdifferential alone is inadequate for understanding automatic differentiation in nonsmooth contexts. Instead, we can sometimes rely on enlarged generalized gradients called "conservative fields", defined through the natural path-wise chain rule: one application is the convergence analysis of gradient-based deep learning algorithms. In the semi-algebraic case, we show that all conservative fields are in fact just Clarke subdifferentials plus normals of manifolds in underlying Whitney stratifications.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 4 of its 13 references that are in the map. First posted on arXiv 3 Jan 2021.

Builds on

4 of 13 references.

References · 4

  1. 2018Stochastic subgradient method converges on tame functionscited by 120
  2. 2019Conservative set valued fields, automatic differentiation, stochastic gradient method and deep learningcited by 71
  3. 2020A mathematical model for automatic differentiation in machine learningcited by 44
  4. 2020On Correctness of Automatic Differentiation for Non-Differentiable Functionscited by 20

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 0; 2025: 1; 2026: 1.

4 papers.