Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
Optimality and Stability in Non-Convex Smooth Games
Authors: Guojun Zhang, Pascal Poupart, Yaoliang Yu
JMLR 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | This paper aims to provide a comprehensive analysis of local minimax points, such as their relation with other solution concepts and their optimality conditions. ... Finally, we study the stability of gradient algorithms near local minimax points. |
| Researcher Affiliation | Academia | Guojun Zhang EMAIL Pascal Poupart EMAIL Yaoliang Yu EMAIL School of Computer Science University of Waterloo Vector Institute |
| Pseudocode | No | The paper does not contain any explicitly labeled pseudocode or algorithm blocks. It focuses on theoretical analysis and mathematical proofs. |
| Open Source Code | No | The paper discusses theoretical concepts and analyses algorithms mathematically but does not provide any information regarding open-source code availability or links to repositories. |
| Open Datasets | No | The paper primarily presents theoretical analysis and mathematical proofs. Although it mentions applications like generative adversarial networks (GANs) and adversarial training as motivations, it does not describe any experiments that utilize specific datasets, nor does it provide concrete access information for any open datasets. |
| Dataset Splits | No | The paper focuses on theoretical research and does not present experiments that use datasets, therefore, no dataset splits are discussed. |
| Hardware Specification | No | The paper is theoretical and does not describe any experimental setup or specify the hardware used for computations. |
| Software Dependencies | No | The paper is theoretical and does not describe any experimental setup or specify software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical, presenting definitions, theorems, and proofs. It does not include an experimental setup section or details about hyperparameters. |