Ideas and Improvements for Semantic Wikis. - Jochen Fischer; Zeno Gantner; Steffen Rendle; Manuel Stritt; Lars Schmidt-Thieme (ESWC, 2006)

Object Identification with Constraints. - Steffen Rendle; Lars Schmidt-Thieme (ICDM, 2006)

Information Integration of Partially Labeled Data. - Steffen Rendle; Lars Schmidt-Thieme (GfKl, 2007)

Active Learning of Equivalence Relations by Minimizing the Expected Loss Using Constraint Inference. - Steffen Rendle; Lars Schmidt-Thieme (ICDM, 2008)

Scaling Record Linkage to Non-uniform Distributed Class Sizes. - Steffen Rendle; Lars Schmidt-Thieme (PAKDD, 2008)

Online-updating regularized kernel matrix factorization models for large-scale recommender systems. - Steffen Rendle; Lars Schmidt-Thieme (RecSys, 2008)

Learning optimal ranking with tensor factorization for tag recommendation. - Steffen Rendle; Leandro Balby Marinho; Alexandros Nanopoulos; Lars Schmidt-Thieme (KDD, 2009)

Learning to Extract Relations for Relational Classification. - Steffen Rendle; Christine Preisach; Lars Schmidt-Thieme (PAKDD, 2009)

Factor Models for Tag Recommendation in BibSonomy. - Steffen Rendle; Lars Schmidt-Thieme (DC@PKDD/ECML, 2009)

BPR: Bayesian Personalized Ranking from Implicit Feedback. - Steffen Rendle; Christoph Freudenthaler; Zeno Gantner; Lars Schmidt-Thieme (UAI, 2009)

Optimal Ranking for Video Recommendation. - Zeno Gantner; Christoph Freudenthaler; Steffen Rendle; Lars Schmidt-Thieme (UCMedia, 2009)

Learning Attribute-to-Feature Mappings for Cold-Start Recommendations. - Zeno Gantner; Lucas Drumond; Christoph Freudenthaler; Steffen Rendle; Lars Schmidt-Thieme (ICDM, 2010)

Factorization Machines. - Steffen Rendle (ICDM, 2010)

Pairwise interaction tensor factorization for personalized tag recommendation. - Steffen Rendle; Lars Schmidt-Thieme (WSDM, 2010)

Factorizing personalized Markov chains for next-basket recommendation. - Steffen Rendle; Christoph Freudenthaler; Lars Schmidt-Thieme (WWW, 2010)

Network effects on interest rates in online social lending. - Ulrik Brandes; Jürgen Lerner; Bobo Nick; Steffen Rendle (GI-Jahrestagung, 2011)

MyMediaLite: a free recommender system library. - Zeno Gantner; Steffen Rendle; Christoph Freudenthaler; Lars Schmidt-Thieme (RecSys, 2011)

Fast context-aware recommendations with factorization machines. - Steffen Rendle; Zeno Gantner; Christoph Freudenthaler; Lars Schmidt-Thieme (SIGIR, 2011)

Context-Aware Ranking with Factorization Models - Steffen Rendle (Springer, 2011)

Recommender Systems for Social Tagging Systems. - Leandro Balby Marinho; Andreas Hotho; Robert Jäschke; Alexandros Nanopoulos; Steffen Rendle; Lars Schmidt-Thieme; Gerd Stumme; Panagiotis Symeonidis (Springer, 2012)

Predicting RDF triples in incomplete knowledge bases with tensor factorization. - Lucas Drumond; Steffen Rendle; Lars Schmidt-Thieme (SAC, 2012)

Learning recommender systems with adaptive regularization. - Steffen Rendle (WSDM, 2012)

Factorization Machines with libFM. - Steffen Rendle (ACM Trans. Intell. Syst. Technol., 2012)

Sample selection for MCMC-based recommender systems. - Thierry Silbermann; Immanuel Bayer; Steffen Rendle (RecSys, 2013)

Scaling Factorization Machines to Relational Data. - Steffen Rendle (Proc. VLDB Endow., 2013)

Improving pairwise learning for item recommendation from implicit feedback. - Steffen Rendle; Christoph Freudenthaler (WSDM, 2014)

Graph Based Relational Features for Collective Classification. - Immanuel Bayer; Uwe Nagel 002; Steffen Rendle (PAKDD (2), 2015)

Robust Large-Scale Machine Learning in the Cloud. - Steffen Rendle; Dennis Fetterly; Eugene J. Shekita; Bor-Yiing Su (KDD, 2016)

A Generic Coordinate Descent Framework for Learning from Implicit Feedback. - Immanuel Bayer; Xiangnan He 001; Bhargav Kanagal; Steffen Rendle (WWW, 2017)

Adaptive Sampled Softmax with Kernel Based Sampling. - Guy Blanc; Steffen Rendle (ICML, 2018)

Efficient Training on Very Large Corpora via Gramian Estimation. - Walid Krichene; Nicolas Mayoraz; Steffen Rendle; Li Zhang 001; Xinyang Yi; Lichan Hong; Ed H. Chi; John R. Anderson (ICLR (Poster), 2019)

On the Difficulty of Evaluating Baselines: A Study on Recommender Systems. - Steffen Rendle; Li Zhang 001; Yehuda Koren (CoRR, 2019)

Evaluation Metrics for Item Recommendation under Sampling. - Steffen Rendle (CoRR, 2019)

Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval. - Tao Wu; Ellie Ka In Chio; Heng-Tze Cheng; Yu Du; Steffen Rendle; Dima Kuzmin; Ritesh Agarwal; Li Zhang 001; John R. Anderson; Sarvjeet Singh; Tushar Chandra; Ed H. Chi; et al. (CIKM, 2020)

Rankmax: An Adaptive Projection Alternative to the Softmax Function. - Weiwei Kong; Walid Krichene; Nicolas Mayoraz; Steffen Rendle; Li Zhang 001 (NeurIPS, 2020)

Neural Collaborative Filtering vs. Matrix Factorization Revisited. - Steffen Rendle; Walid Krichene; Li Zhang 001; John R. Anderson (RecSys, 2020)

Superbloom: Bloom filter meets Transformer. - John R. Anderson; Qingqing Huang; Walid Krichene; Steffen Rendle; Li Zhang 001 (CoRR, 2020)

Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates. - Steve Chien; Prateek Jain 002; Walid Krichene; Steffen Rendle; Shuang Song 001; Abhradeep Thakurta; Li Zhang 001 (ICML, 2021)

On Sampled Metrics for Item Recommendation (Extended Abstract). - Walid Krichene; Steffen Rendle (IJCAI, 2021)

Item Recommendation from Implicit Feedback. - Steffen Rendle (CoRR, 2021)

iALS++: Speeding up Matrix Factorization with Subspace Optimization. - Steffen Rendle; Walid Krichene; Li Zhang 001; Yehuda Koren (CoRR, 2021)

ALX: Large Scale Matrix Factorization on TPUs. - Harsh Mehta; Steffen Rendle; Walid Krichene; Li Zhang 001 (CoRR, 2021)

Revisiting the Performance of iALS on Item Recommendation Benchmarks. - Steffen Rendle; Walid Krichene; Li Zhang 001; Yehuda Koren (RecSys, 2022)

On sampled metrics for item recommendation. - Walid Krichene; Steffen Rendle (Commun. ACM, 2022)

Advances in Collaborative Filtering. - Yehuda Koren; Steffen Rendle; Robert M. Bell (Recommender Systems Handbook, 2022)

Item Recommendation from Implicit Feedback. - Steffen Rendle (Recommender Systems Handbook, 2022)

Answering Compositional Queries with Set-Theoretic Embeddings. - Shib Sankar Dasgupta; Andrew McCallum; Steffen Rendle; Li Zhang (CoRR, 2023)

Training Differentially Private Ad Prediction Models With Semi-Sensitive Features. - Lynn Chua; Qiliang Cui; Badih Ghazi; Charlie Harrison; Pritish Kamath; Walid Krichene; Ravi Kumar 001; Pasin Manurangsi; Nicolas Mayoraz; Hema Venkata Krishna Giri Narra; Steffen Rendle; Amer Sinha; et al. (AdKDD@KDD, 2024)

Private Learning with Public Features. - Walid Krichene; Nicolas Mayoraz; Steffen Rendle; Shuang Song 001; Abhradeep Thakurta; Li Zhang 001 (AISTATS, 2024)

Improved Estimation of Ranks for Learning Item Recommenders with Negative Sampling. - Anushya Subbiah; Steffen Rendle; Vikram Aggarwal (CIKM, 2024)

Efficient Optimization of Sparse User Encoder Recommenders. - Steffen Rendle (Trans. Recomm. Syst., 2024)