| BPR: Bayesian personalized ranking from implicit feedback S Rendle, C Freudenthaler, Z Gantner, L Schmidt-Thieme arXiv preprint arXiv:1205.2618, 2012 | 7589 | 2012 |
| Factorization machines S Rendle 2010 IEEE International conference on data mining, 995-1000, 2010 | 3635 | 2010 |
| Factorizing personalized markov chains for next-basket recommendation S Rendle, C Freudenthaler, L Schmidt-Thieme Proceedings of the 19th international conference on World wide web, 811-820, 2010 | 2688 | 2010 |
| Advances in collaborative filtering Y Koren, S Rendle, R Bell Recommender systems handbook, 91-142, 2021 | 2052 | 2021 |
| Factorization machines with libfm S Rendle ACM Transactions on Intelligent Systems and Technology (TIST) 3 (3), 1-22, 2012 | 1603 | 2012 |
| Pairwise interaction tensor factorization for personalized tag recommendation S Rendle, L Schmidt-Thieme Proceedings of the third ACM international conference on Web search and data …, 2010 | 884 | 2010 |
| Fast context-aware recommendations with factorization machines S Rendle, Z Gantner, C Freudenthaler, L Schmidt-Thieme Proceedings of the 34th international ACM SIGIR conference on Research and …, 2011 | 749 | 2011 |
| MyMediaLite: A free recommender system library Z Gantner, S Rendle, C Freudenthaler, L Schmidt-Thieme Proceedings of the fifth ACM conference on Recommender systems, 305-308, 2011 | 535 | 2011 |
| On sampled metrics for item recommendation W Krichene, S Rendle Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 517 | 2020 |
| Neural collaborative filtering vs. matrix factorization revisited S Rendle, W Krichene, L Zhang, J Anderson Proceedings of the 14th ACM Conference on Recommender Systems, 240-248, 2020 | 484 | 2020 |
| Learning optimal ranking with tensor factorization for tag recommendation S Rendle, L Balby Marinho, A Nanopoulos, L Schmidt-Thieme Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009 | 478 | 2009 |
| Improving pairwise learning for item recommendation from implicit feedback S Rendle, C Freudenthaler Proceedings of the 7th ACM international conference on Web search and data …, 2014 | 457 | 2014 |
| Learning attribute-to-feature mappings for cold-start recommendations Z Gantner, L Drumond, C Freudenthaler, S Rendle, L Schmidt-Thieme 2010 IEEE international conference on data mining, 176-185, 2010 | 397 | 2010 |
| Online-updating regularized kernel matrix factorization models for large-scale recommender systems S Rendle, L Schmidt-Thieme Proceedings of the 2008 ACM conference on Recommender systems, 251-258, 2008 | 320 | 2008 |
| A generic coordinate descent framework for learning from implicit feedback I Bayer, X He, B Kanagal, S Rendle Proceedings of the 26th international conference on world wide web, 1341-1350, 2017 | 267 | 2017 |
| On the difficulty of evaluating baselines: A study on recommender systems S Rendle, L Zhang, Y Koren arXiv preprint arXiv:1905.01395, 2019 | 150 | 2019 |
| Scaling factorization machines to relational data S Rendle Proceedings of the VLDB Endowment 6 (5), 337-348, 2013 | 139 | 2013 |
| Factorization models for context-/time-aware movie recommendations Z Gantner, S Rendle, L Schmidt-Thieme Proceedings of the workshop on context-aware movie recommendation, 14-19, 2010 | 115 | 2010 |
| Adaptive sampled softmax with kernel based sampling G Blanc, S Rendle International conference on machine learning, 590-599, 2018 | 92 | 2018 |
| BPR: Bayesian personalized ranking from implicit feedback. arXiv 2012 S Rendle, C Freudenthaler, Z Gantner, L Schmidt-Thieme arXiv preprint arXiv:1205.2618, 2012 | 82 | 2012 |
