Scaling Factorization Machines to Relational Data
Summary: Exploits relational design-matrix patterns to scale factorization machines on relational data. Adapts coordinate descent and Bayesian MCMC for linear regression and FM, showing scalability on Netflix/KDDCup and competitive with task-specific models. (summarized by gpt-5-nano on Feb 09 2026)
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