Robotics paper index

Lipschitzian SLLNs for random functions

2026-07-22 · arXiv: 2607.20411

One-line summary

A robotics research paper on Lipschitzian SLLNs for random functions.

Engineering notes

Engineering notes will be added by the Robot Papers editorial team.

Chinese explanation / 中文解读

中文解读待补充:本站会优先为 VLA、具身智能、人形机器人控制、机器人操作等高价值论文补充中文说明。

Original abstract

We prove strong laws of large numbers for locally Lipschitz functions in the Lipschitz pseudometric. Our results hold under either a topological or a model-theoretic condition, with the latter encompassing functions jointly definable in o-minimal structures but extending substantially beyond this class. Applications include uniform convergence of limiting and Clarke subdifferentials and finite-sample identification of solutions. Consequently, we identify broad classes of functions for which the failure phenomena revealed by our previous negative results [Tian and Royset, arXiv:2511.16568, 2025] do not occur.

5.0Engineering value
7.0Research novelty
4.0Business relevance

Links and sources

Need this topic turned into a technical roadmap?

Robot Papers can prepare a custom robotics literature review, code map, dataset map, and B2B technology assessment.

Request B2B research

Comments

No comments yet. Be the first to share your thoughts on this paper.
Login or register to leave a comment