Elementary superexpressive activations
Authors: Dmitry Yarotsky
ICML 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | First, our existence result (Theorem 3) is of course purely theoretical: though the network is small, a huge approximation complexity is hidden in the very special choice of the network weights. |
| Researcher Affiliation | Academia | 1Skolkovo Institute of Science and Technology, Moscow, Russia. Correspondence to: Dmitry Yarotsky <d.yarotsky@skoltech.ru>. |
| Pseudocode | No | The paper does not contain any pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | No | This paper is theoretical and does not describe a methodology with associated source code for release. |
| Open Datasets | No | This is a theoretical paper and does not describe experiments using a dataset, hence no information about dataset availability for training. |
| Dataset Splits | No | This is a theoretical paper and does not describe experiments requiring training/validation/test splits. |
| Hardware Specification | No | This is a theoretical paper and does not describe experiments, thus no hardware specifications are mentioned. |
| Software Dependencies | No | This is a theoretical paper and does not describe experiments, thus no software dependencies are mentioned. |
| Experiment Setup | No | This is a theoretical paper and does not describe any experimental setup or hyperparameters. |