https://github.com/hibayesian/spark-optim
A library of scalable optimization algorithms based on Spark
https://github.com/hibayesian/spark-optim
machine-learning optimization-algorithms spark
Last synced: 7 months ago
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A library of scalable optimization algorithms based on Spark
- Host: GitHub
- URL: https://github.com/hibayesian/spark-optim
- Owner: hibayesian
- License: apache-2.0
- Created: 2017-06-02T15:12:29.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2017-07-09T08:39:36.000Z (over 8 years ago)
- Last Synced: 2025-04-08T19:33:29.512Z (11 months ago)
- Topics: machine-learning, optimization-algorithms, spark
- Language: Scala
- Size: 18.6 KB
- Stars: 8
- Watchers: 0
- Forks: 4
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Spark-Optim
Spark-Optim is a library of scalable optimization algorithms based on Spark. It is designed to provide optimization algorithms which are recently published or widely used but have not been implemented in Spark MLlib.
# Highlight
Currently, Spark-Optim provides following implementations.
+ Parallel Stochastic Gradient Descent [[reference]](http://research.cs.rutgers.edu/~lihong/pub/Zinkevich11Parallelized.pdf)
+ Parallel Follow-the-regularized-leader [[reference]](https://www.eecs.tufts.edu/~dsculley/papers/ad-click-prediction.pdf)
# Requirements
Spark-Optim is built against Spark 2.1.1.
# Build From Source
```scala
sbt package
```
# Licenses
Spark-Optim is available under Apache Licenses 2.0.
# Contact & Feedback
If you encounter bugs, feel free to submit an issue or pull request. Also you can mail to:
+ hibayesian (hibayesian@gmail.com).