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Factorization Machines (FM) are only used in a narrow range of applications and are not part of the standard toolbox of machine learning models.
Maximum-margin matrix factorization
Nathan Srebro, Jason Rennie, and Tommi S Jaakkola · 2004
Earlier work this paper cites.
Validation of software for bayesian models using posterior quantiles
Samantha R Cook, Andrew Gelman, and Donald B Rubin · 2006
Earlier work this paper cites.
Direct methods for sparse linear systems , volume 2
Timothy A Davis · 2006
Earlier work this paper cites.
Factor models for tag recommendation in bibsonomy
Steffen Rendle and Lars Schmidt-Thieme · 2009
Earlier work this paper cites.
Bpr: Bayesian personalized ranking from implicit feedback
Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme · 2009
Cited alongside, same era.
Cython: The best of both worlds
Stefan Behnel, Robert Bradshaw, Craig Citro, Lisandro Dalcin, Dag Sverre Seljebotn, and Kurt Smith · 2011
Cited alongside, same era.
Bayesian factorization machines
Christoph Freudenthaler, Lars Schmidt-thieme, and Steffen Rendle · 2011
Cited alongside, same era.
Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
Cited alongside, same era.
Social network and click-through prediction with factorization machines
Steffen Rendle
Cited in the paper.
Factorization machines with libFM
Steffen Rendle
Cited in the paper.
Svdfeature: a toolkit for feature-based collaborative filtering
Tianqi Chen, Weinan Zhang, Qiuxia Lu, Kailong Chen, Zhao Zheng, and Yong Yu · 2012
Later among the works it cites.
Factor models for recommending given names
Immanuel Bayer and Steffen Rendle · 2013
Later among the works it cites.
Bidmach: Large-scale learning with zero memory allocation
John Canny and Huasha Zhao · 2013
Later among the works it cites.
Graphlab: A new framework for parallel machine learning
Yucheng Low, Joseph E Gonzalez, Aapo Kyrola, Danny Bickson, Carlos E Guestrin, and Joseph Hellerstein · 2014
Later among the works it cites.
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