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Nakul Jindal commented on SYSTEMML-1437: ---------------------------------------- Hi [~rakesh_chinta], [~anantbietec], If you guys have submitted a proposal to GSoC, could you please paste the title here? I found a proposal by Rakesh titled "Apache GSOC Project Proposal". [~rakesh_chinta] - is the proposal for this project? [~anantbietec] - have you submitted any proposals? > 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] -- This message was sent by Atlassian JIRA (v6.3.15#6346)