Proximal Gradient Descent-Ascent: Variable Convergence under KŁ Geometry
Authors: Ziyi Chen, Yi Zhou, Tengyu Xu, Yingbin Liang
ICLR 2021 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | This is the first theoretical result on the variable convergence for nonconvex minimax optimization. |
| Researcher Affiliation | Academia | Ziyi Chen, Yi Zhou Department of ECE University of Utah Salt Lake City, UT 84112, USA EMAIL. Tengyu Xu, Yingbin Liang Department of ECE The Ohio State University Columbus, OH 43210, USA EMAIL |
| Pseudocode | Yes | Algorithm 1 Proximal-GDA |
| Open Source Code | No | The paper does not provide any statement or link regarding the release of source code for the methodology described. |
| Open Datasets | No | This is a theoretical paper and does not use or reference any datasets for training. |
| Dataset Splits | No | This is a theoretical paper and does not specify training/validation/test dataset splits. |
| Hardware Specification | No | This is a theoretical paper and does not report on experiments, thus no hardware specifications are provided. |
| Software Dependencies | No | This is a theoretical paper and does not report on experiments or provide specific software dependencies with version numbers. |
| Experiment Setup | No | This is a theoretical paper and does not describe any experimental setup details. |