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optimization

Reproducible results for the various types of optimization techniques I have implemented

https://github.com/beegass/optimization

Science Score: 57.0%

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    Found .zenodo.json file
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    Found 1 DOI reference(s) in README
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    Low similarity (7.1%) to scientific vocabulary
Last synced: 7 months ago · JSON representation ·

Repository

Reproducible results for the various types of optimization techniques I have implemented

Basic Info
  • Host: GitHub
  • Owner: BeeGass
  • License: other
  • Language: Python
  • Default Branch: master
  • Size: 86.9 KB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 4 years ago · Last pushed about 4 years ago
Metadata Files
Readme License Citation

README.md

Optimization
Jax - Julia

A collection of optimization techniques I have implemented in jax and flux with particular effort put into readability and reproducibility.

Python

Requirements For Jax

  • Python >= 3.8
  • jax

Installation

$ git clone https://github.com/BeeGass/Readable-Optimization.git

Usage

$ cd Readable-Optimization/vae-jax $ python main.py

Julia

Requirements For Flux

  • TODO
  • TODO

Usage

``` $ cd Readable-Optimization/vae-flux $ # TBA

```

Config File Template yaml TBA

First Order Results

| Model | Jax/Flax | Flux | Config | Paper | Animations | Samples | |:--------------------------------------- |:--------:|:-------:|:-------:|:-------- |:----------:|:-------:| | Gradient Descent | ☐ | ☐ | ☐ | Link | TBA | TBA | | Stochastic Gradient Descent | ☐ | ☐ | ☐ | Link | TBA | TBA | | Batch Gradient Descent | ☐ | ☐ | ☐ | Link | TBA | TBA | | Mini-Batch Gradient Descent | ☐ | ☐ | ☐ | Link | TBA | TBA | | SGD w/ Momentum | ☐ | ☐ | ☐ | Link | TBA | TBA | | Nesterov's Gradient Acceleration | ☐ | ☐ | ☐ | Link | TBA | TBA | | AdaGrad(Adaptive Gradient Descent) | ☐ | ☐ | ☐ | Link | TBA | TBA | | AdaDelta | ☐ | ☐ | ☐ | Link | TBA | TBA | | RMS-Prop (Root Mean Square Propagation) | ☐ | ☐ | ☐ | Link | TBA | TBA | | Adam(Adaptive Moment Estimation) | ☐ | ☐ | ☐ | Link | TBA | TBA | | Adamw | ☐ | ☐ | ☐ | Link | TBA | TBA |

Second Order Results

| Model | Jax/Flax | Flux | Config | Paper | Animations | Samples | |:--------------------------------------- |:--------:|:-------:|:-------:|:-------- |:----------:|:-------:| | Newton's Method | ☐ | ☐ | ☐ | Link | TBA | TBA | | Secant Method | ☐ | ☐ | ☐ | Link | TBA | TBA | | Davidson-Fletcher-Powell (DFP) | ☐ | ☐ | ☐ | Link | TBA | TBA | | Broyden-Fletcher-Goldfarb-Shanno (BFGS) | ☐ | ☐ | ☐ | Link | TBA | TBA | | Limited-memory BFGS (L-BFGS) | ☐ | ☐ | ☐ | Link | TBA | TBA | | Newton-Raphson | ☐ | ☐ | ☐ | Link | TBA | TBA | | Levenberg-Marquardt | ☐ | ☐ | ☐ | Link | TBA | TBA | | Powell's method | ☐ | ☐ | ☐ | Link | TBA | TBA | | Steepest Descent | ☐ | ☐ | ☐ | Link | TBA | TBA | | Truncated Newton | ☐ | ☐ | ☐ | Link | TBA | TBA | | Fletcher-Reeves | ☐ | ☐ | ☐ | Link | TBA | TBA |

Citation

bib @software{B_Gass_Optimization_2022, author = {B Gass, B Gass}, doi = {10.5281/zenodo.1234}, month = {1}, title = {{Readable-Optimization}}, url = {https://github.com/BeeGass/Optimization}, version = {1.0.0}, year = {2022} }

Owner

  • Name: Bryan
  • Login: BeeGass
  • Kind: user
  • Location: Cambridge, MA
  • Company: @USArmyResearchLab

Research Engineer interested in SSMs

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "B Gass"
  given-names: "B Gass"
  orcid: "https://orcid.org/0000-0000-0000-0000"
title: "Optimization"
version: 1.0.0
doi: 10.5281/zenodo.1234
date-released: 2022-01-08
url: "https://github.com/BeeGass/Optimization"

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