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https://issues.apache.org/jira/browse/SYSTEMML-1437?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15949297#comment-15949297
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Nakul Jindal commented on SYSTEMML-1437:
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Hi [~return_01], the goal of this project, if successful is to be able to use
your implementation to grow the SystemML DML library and showcase the
scalability of SystemML by creating an end-to-end recommendation system.
Ideally, your implementation would be in the SystemML's domain specific
language - DML, which is R like. We haven't considered it being done in other
languages. However, if you are really interested in doing it in C++, take a
look at SystemML, how it functions and if you did factorization machines in
C++, how it would integrate back into SystemML or showcase SystemML's
scalability; then write a proposal with your project idea.
> Implement and scale Factorization Machines using SystemML
> ---------------------------------------------------------
>
> Key: SYSTEMML-1437
> URL: https://issues.apache.org/jira/browse/SYSTEMML-1437
> Project: SystemML
> Issue Type: Task
> Reporter: Imran Younus
> Labels: factorization_machines, gsoc2017, machine_learning,
> mentor, recommender_system
>
> Factorization Machines have gained popularity in recent years due to their
> effectiveness in recommendation systems. FMs are general predictors which
> allow to capture interactions between all features in a features matrix. The
> feature matrices pertinent to the recommendation systems are highly sparse.
> SystemML's highly efficient distributed sparse matrix operations can be
> leveraged to implement FMs in a scalable fashion. Given the closed model
> equation of FMs, the model parameters can be learned using gradient descent
> methods.
> This project aims to implement FMs as described in the first paper:
> http://www.algo.uni-konstanz.de/members/rendle/pdf/Rendle2010FM.pdf
> We'll showcase the scalability of SystemML implementation of FMs by creating
> an end-to-end recommendation system.
> Basic understanding of machine learning and optimization techniques is
> required. Will need to collaborate with the team to resolve scaling and other
> systems related issues.
> Rating: Medium
> Mentors: [~iyounus], [~nakul02]
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