https://github.com/tommoral/adaptiveoptim

Adaptive optimization procedure
https://github.com/tommoral/adaptiveoptim

Last synced: 7 days ago
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Adaptive optimization procedure

• Host: GitHub
• URL: https://github.com/tommoral/adaptiveoptim
• Owner: tomMoral
• Created: 2016-07-14T09:49:02.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2018-04-09T18:02:22.000Z (over 6 years ago)
• Last Synced: 2024-11-02T09:51:37.004Z (14 days ago)
• Language: Python
• Size: 93.8 KB
• Stars: 16
• Watchers: 5
• Forks: 8
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

        
# AdaptiveOptim

Source code for the experiments and figures of the paper ["Adaptive Acceleration of Sparse Coding via Matrix Factorization "](https://arxiv.org/abs/1609.00285). 

### Requirements

 * numpy 1.10+

 * matplotlib 1.8+

 * tensorflow 0.9+

 * scikit-learn 1.16+

All the development was done with python3.4 and might not work for earlier versions.

### Usage

Use the main script `NIPS_figures.py` to launch the experiements. Various option are available from the command line. See `python NIPS_figures.py --help` for more information.

To generate the 4 figures from the paper, use:

```bash

python NIPS_figures.py --data artificial --save_dir layer1

python NIPS_figures.py --data artificial --rho .2 --save_dir layer2

python NIPS_figures.py --data mnist --lmbd .1 -K 100 --save_dir mnist

python NIPS_figures.py --data images --lmbd .05 --save_dir images

```