Conservative and semismooth derivatives are equivalent for semialgebraic maps
Not on the map. Why?
Abstract (arXiv)
Subgradient and Newton algorithms for nonsmooth optimization require generalized derivatives to satisfy subtle approximation properties: conservativity for the former and semismoothness for the latter. Though these two properties originate in entirely different contexts, we show that in the semi-algebraic setting they are equivalent. Both properties for a generalized derivative simply require it to coincide with the standard directional derivative on the tangent spaces of some partition of the domain into smooth manifolds. An appealing byproduct is a new short proof that semi-algebraic maps are semismooth relative to the Clarke Jacobian.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Feb 2021.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 0; 2024: 0; 2025: 0; 2026: 1.
4 papers.
- 2021Nonsmooth Implicit Differentiation for Machine Learning and Optimizationcited by 43
- 2022On the complexity of nonsmooth automatic differentiationcited by 4
- 2022Path differentiability of ODE flowscited by 1
- 2026Efficient and provably convergent end-to-end training of deep neural networks with linear constraintscited by 0
- 2026Efficient and provably convergent end-to-end training of deep neural networks with linear constraints12 May 2026
- 2022On the complexity of nonsmooth automatic differentiation1 Jun 2022
- 2022Path differentiability of ODE flows11 Jan 2022
- 2021Nonsmooth Implicit Differentiation for Machine Learning and Optimization8 Jun 2021