# Frank-Wolfe Style Algorithms for Large Scale Optimization

arXiv: https://arxiv.org/abs/1808.05274 · HTML: https://mlsanity.com/paper/1808.05274/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Aug 2018.

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

- [Projection-Free CNN Pruning via Frank-Wolfe with Momentum: Sparser Models with Less Pretraining](https://mlsanity.com/paper/2512.01147/) (2025)

## Abstract (arXiv)

We introduce a few variants on Frank-Wolfe style algorithms suitable for large scale optimization. We show how to modify the standard Frank-Wolfe algorithm using stochastic gradients, approximate subproblem solutions, and sketched decision variables in order to scale to enormous problems while preserving (up to constants) the optimal convergence rate O(frac1k).