This repository is the official implementation of Appendix D in the supplementary material of the paper, Improved Bounds on Neural Complexity for Representing Piecewise Linear Functions.
- Download the paper from NeurIPS website or arXiv.
To install requirements:
pip install -r requirements.txt
Please install Python before running the above setup command. The code was tested on Python 3.9.13.
To measure the run time of Algorithm 1, run:
python main.py
The results will be saved to a CSV file.
The run time is reported in seconds.
| n=1 | n=10 | n=100 | |
|---|---|---|---|
| q=1 | 0.0007 | 0.0009 | 0.0013 |
| q=2 | 0.0034 | 0.0075 | 0.0083 |
| q=4 | 0.0097 | 0.0248 | 0.0343 |
| q=8 | 0.0336 | 0.0980 | 0.1253 |
| q=16 | 0.1212 | 0.3932 | 0.4795 |
| q=32 | 0.4663 | 1.5408 | 1.8860 |
@inproceedings{chen2022improved,
title={Improved Bounds on Neural Complexity for Representing Piecewise Linear Functions},
author={Chen, Kuan-Lin and Garudadri, Harinath and Rao, Bhaskar D.},
booktitle={Advances in Neural Information Processing Systems (NeurIPS)},
year={2022}
}