Scalable Convex Neural Networks: a package for fasts convex optimization of shallow neural networks.
Project description
scnn: Scalable Convex Neural Networks
A library for global optimization of shallow neural networks. API documentation at ReadTheDocs.
Requirements
Python 3.8 or newer. Development dependencies are listed in dev_requirements.txt.
Setup
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
Contributions
Coming soon!
Citation
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.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file pyscnn-0.0.10.tar.gz.
File metadata
- Download URL: pyscnn-0.0.10.tar.gz
- Upload date:
- Size: 80.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
6f511f6620984013bb98e4b12c6b350a4151a8ca178af64c8f38679775787e06
|
|
| MD5 |
35898128534b1291302951897bc2d2b2
|
|
| BLAKE2b-256 |
052f2eb1b159eb20111324a82303e2654ac0475ca72260c35386e4160393561e
|
File details
Details for the file pyscnn-0.0.10-py3-none-any.whl.
File metadata
- Download URL: pyscnn-0.0.10-py3-none-any.whl
- Upload date:
- Size: 123.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
a194f150078a07a42eb15240f6e13bea7780cbd2e94bbcceaf37ae7a13075a23
|
|
| MD5 |
b2e1d3ecf16798c314530163f284cf7c
|
|
| BLAKE2b-256 |
b7b428b088d7bb66021c8c1ecdcceffd28cceefbe878ec5261d7ac5a81f08101
|