# Convergence of a Stochastic Subgradient Method with Averaging for Nonsmooth Nonconvex Constrained Optimization

arXiv: https://arxiv.org/abs/1912.07580 · HTML: https://mlsanity.com/paper/1912.07580/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Dec 2019.

## Built on by (most cited first, 10 of 10)

- [Policy Gradient Method For Robust Reinforcement Learning](https://mlsanity.com/paper/2205.07344/) (2022)
- [A Two-Time-Scale Stochastic Optimization Framework with Applications in Control and Reinforcement Learning](https://mlsanity.com/paper/2109.14756/) (2021)
- [Langevin dynamics based algorithm e-THvarepsilonO POULA for stochastic optimization problems with discontinuous stochastic gradient](https://mlsanity.com/paper/2210.13193/) (2022)
- [Adam-family Methods with Decoupled Weight Decay in Deep Learning](https://mlsanity.com/paper/2310.08858/) (2023)
- [A Functional Model Method for Nonconvex Nonsmooth Conditional Stochastic Optimization](https://mlsanity.com/paper/2405.10815/) (2024)
- [Stochastic Subgradient Methods with Guaranteed Global Stability in Nonsmooth Nonconvex Optimization](https://mlsanity.com/paper/2307.10053/) (2023)
- [Developing Lagrangian-based Methods for Nonsmooth Nonconvex Optimization](https://mlsanity.com/paper/2404.09438/) (2024)
- [Stochastic Nested Compositional Bi-level Optimization for Robust Feature Learning](https://mlsanity.com/paper/2307.05384/) (2023)
- [Convergence of Decentralized Stochastic Subgradient-based Methods for Nonsmooth Nonconvex functions](https://mlsanity.com/paper/2403.11565/) (2024)
- [Optimal Algorithms for Nonsmooth Nonconvex Stochastic Optimization with Constraints](https://mlsanity.com/paper/2610.13787/) (2026)

## Abstract (arXiv)

We prove convergence of a single time-scale stochastic subgradient method with subgradient averaging for constrained problems with a nonsmooth and nonconvex objective function having the property of generalized differentiability. As a tool of our analysis, we also prove a chain rule on a path for such functions.