# Approximate Last Iterate Convergence in Overparameterized GANs

arXiv: https://arxiv.org/abs/2108.03491 · HTML: https://mlsanity.com/paper/2108.03491/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 3 references that are in the map.
- First posted on arXiv 7 Aug 2021.

## Builds on (most cited first, 3 of 3)

- [Neural Tangent Kernel: Convergence and Generalization in Neural Networks](https://mlsanity.com/paper/1806.07572/) (2018)
- [Interaction Matters: A Note on Non-asymptotic Local Convergence of Generative Adversarial Networks](https://mlsanity.com/paper/1802.06132/) (2018)
- [Provably Efficient Neural Estimation of Structural Equation Model: An Adversarial Approach](https://mlsanity.com/paper/2007.01290/) (2020)

## Abstract (arXiv)

In this work, we showed that the Implicit Update and Predictive Methods dynamics introduced in prior work satisfy last iterate convergence to a neighborhood around the optimum in overparameterized GANs, where the size of the neighborhood shrinks with the width of the neural network. This is in contrast to prior results, which only guaranteed average iterate convergence.