# Primal-dual subgradient method for constrained convex optimization problems

arXiv: https://arxiv.org/abs/2009.12769 · HTML: https://mlsanity.com/paper/2009.12769/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Sep 2020.

## Built on by (most cited first, 1 of 1)

- [Comparing different subgradient methods for solving convex optimization problems with functional constraints](https://mlsanity.com/paper/2101.01045/) (2021)

## Abstract (arXiv)

This paper considers a general convex constrained problem setting where functions are not assumed to be differentiable nor Lipschitz continuous. Our motivation is in finding a simple first-order method for solving a wide range of convex optimization problems with minimal requirements. We study the method of weighted dual averages (Nesterov, 2009) in this setting and prove that it is an optimal method.