Skip to main content

A globally convergent fast iterative shrinkage-thresholding algorithm with a new momentum factor for single and multi-objective convex optimization

Project description

# zfista : A globally convergent fast iterative shrinkage-thresholding algorithm with a new momentum factor for single and multi-objective convex optimization

This code repository includes the source code for the [Paper](http://example.com “Preparing”)

` A globally convergent fast iterative shrinkage-thresholding algorithm with a new momentum factor for single and multi-objective convex optimization Hiroki Tanabe, Ellen H. Fukuda, and Nobuo Yamashita `

## Requirements - Python 3.5 or later

## Examples You can run some examples on jupyter notebooks. `sh jupyter notebook `

## For developers To set up development environment, run `sh python -m venv venv source venv/bin/activate python -m pip install --upgrade pip pip install -r requirements.txt `

## Testing You can run all tests by `sh python -m unittest discover `

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

zfista-0.0.1.tar.gz (6.9 kB view hashes)

Uploaded Source

Built Distribution

zfista-0.0.1-py3-none-any.whl (7.1 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page