| BPR: Bayesian personalized ranking from implicit feedback S Rendle, C Freudenthaler, Z Gantner, L Schmidt-Thieme arXiv preprint arXiv:1205.2618, 2012 | 9186 | 2012 |
| 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 | 3263 | 2010 |
| 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 | 913 | 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 | 794 | 2011 |
| Tag recommendations in folksonomies R Jäschke, L Marinho, A Hotho, L Schmidt-Thieme, G Stumme European conference on principles of data mining and knowledge discovery …, 2007 | 759 | 2007 |
| Learning time-series shapelets J Grabocka, N Schilling, M Wistuba, L Schmidt-Thieme Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 671 | 2014 |
| 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 | 553 | 2011 |
| Tag-aware recommender systems by fusion of collaborative filtering algorithms KHL Tso-Sutter, LB Marinho, L Schmidt-Thieme Proceedings of the 2008 ACM symposium on Applied computing, 1995-1999, 2008 | 530 | 2008 |
| Cost-sensitive learning methods for imbalanced data N Thai-Nghe, Z Gantner, L Schmidt-Thieme The 2010 International joint conference on neural networks (IJCNN), 1-8, 2010 | 507 | 2010 |
| 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 | 473 | 2009 |
| Recommender system for predicting student performance N Thai-Nghe, L Drumond, A Krohn-Grimberghe, L Schmidt-Thieme Procedia Computer Science 1 (2), 2811-2819, 2010 | 429 | 2010 |
| 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 | 416 | 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 | 329 | 2008 |
| Learning taxonomic relations from heterogeneous sources of evidence P Cimiano, A Pivk, L Schmidt-Thieme, S Staab Ontology Learning from Text: Methods, evaluation and applications 123, 59-73, 2005 | 327* | 2005 |
| Beyond manual tuning of hyperparameters F Hutter, J Lücke, L Schmidt-Thieme KI-Künstliche Intelligenz 29 (4), 329-337, 2015 | 300 | 2015 |
| Taxonomy-driven computation of product recommendations CN Ziegler, G Lausen, L Schmidt-Thieme Proceedings of the thirteenth ACM international conference on Information …, 2004 | 298 | 2004 |
| Tag recommendations in social bookmarking systems R Jäschke, L Marinho, A Hotho, L Schmidt-Thieme, G Stumme Ai Communications 21 (4), 231-247, 2008 | 264 | 2008 |
| Do we really need deep learning models for time series forecasting? S Elsayed, D Thyssens, A Rashed, HS Jomaa, L Schmidt-Thieme arXiv preprint arXiv:2101.02118, 2021 | 244 | 2021 |
| Multi-relational matrix factorization using bayesian personalized ranking for social network data A Krohn-Grimberghe, L Drumond, C Freudenthaler, L Schmidt-Thieme Proceedings of the fifth ACM international conference on Web search and data …, 2012 | 239 | 2012 |
| Real-time top-n recommendation in social streams E Diaz-Aviles, L Drumond, L Schmidt-Thieme, W Nejdl Proceedings of the sixth ACM conference on Recommender systems, 59-66, 2012 | 218 | 2012 |
Steffen RendleGoogleVerified email at google.com
