Steffen Rendle

Steffen Rendle is a person.

• See: BPR Algorithm, libFM.

---

---

References

• http://scholar.google.com/citations?user=yR-ugIoAAAAJ
• http://dblp.uni-trier.de/pers/hd/r/Rendle:Steffen

2020

• (Krichene & Rendle, 2020) ⇒ Walid Krichene, and Steffen Rendle. (2020). “On Sampled Metrics for Item Recommendation.” In: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD-2020).

2019

• (Rendle et al., 2019) ⇒ Steffen Rendle, Li Zhang, and Yehuda Koren. (2019). “On the Difficulty of Evaluating Baselines: A Study on Recommender Systems.” In: arXiv preprint arXiv:1905.01395.

2014

• (Rendle & Freudenthaler, 2014) ⇒ Steffen Rendle, and Christoph Freudenthaler. (2014). “Improving Pairwise Learning for Item Recommendation from Implicit Feedback.” In: Proceedings of the 7th ACM International Conference on Web search and data mining. ISBN:978-1-4503-2351-2 doi:10.1145/2556195.2556248

2010

• (Rendle, 2010) ⇒ Steffen Rendle. (2010). “Factorization Machines.” In: Proceedings of the 2010 IEEE International Conference on Data Mining. ISBN:978-0-7695-4256-0 doi:10.1109/ICDM.2010.127

2009a

• (Rendle et al., 2009a) ⇒ Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. (2009). “BPR: Bayesian Personalized Ranking from Implicit Feedback.” In: Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence. ISBN:978-0-9749039-5-8

2009b

• (Rendle et al., 2009b) ⇒ Steffen Rendle, Leandro Balby Marinho, Alexandros Nanopoulos, and Lars Schmidt-Thieme. (2009). “Learning Optimal Ranking with Tensor Factorization for Tag Recommendation.” In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2009). doi:10.1145/1557019.1557100

2008

• (Rendle & Schmidt-Thieme, 2008) ⇒ Steffen Rendle, and Lars Schmidt-Thieme. (2008). “Online-updating Regularized Kernel Matrix Factorization Models for Large-scale Recommender Systems.” In: Proceedings of the 2008 ACM conference on Recommender systems. ISBN:978-1-60558-093-7 doi:10.1145/1454008.1454047

---