A library for global optimization of shallow neural networks. API documentation at ReadTheDocs.
Python 3.8 or newer. Development dependencies are listed in dev_requirements.txt.
Install using pip:
python -m pip install pyscnn
Or, clone the repository and manually install:
git clone https://github.com/pilancilab/scnn.git
python -m pip install ./scnn
Coming soon!
Please cite our paper if you use this package.
@article{DBLP:journals/corr/abs-2202-01331,
author = {Aaron Mishkin and
Arda Sahiner and
Mert Pilanci},
title = {Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model
Classes and Cone Decompositions},
journal = {CoRR},
volume = {abs/2202.01331},
year = {2022},
url = {https://arxiv.org/abs/2202.01331},
}
Looking for the code to replicate our experiments? See scnn_experiments.
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