Scaling Factorization Machines to Relational Data
Summary: Exploits repeated design-matrix patterns induced by high-cardinality relational data to scale coordinate descent and Bayesian MCMC for regression and factorization machines. Matches specialized Netflix/KDDCup models while avoiding infeasible explicit matrices. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Steffen Rendle (University of Konstanz)
BibTeX Citation
@article{rendle_vldb13,
title = {{Scaling Factorization Machines to Relational Data}},
author = {Rendle, Steffen},
journal = {PVLDB},
series = {{VLDB} '13},
volume = {6},
number = {5},
pages = {337--348},
doi = {10.14778/2535573.248},
url = {https://doi.org/10.14778/2535573.248},
year = {2013}
}
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