Steffen Rendle

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 30

Top Topics

Item Recommendation

Matrix Factorization

Implicit Feedback

Recommender Systems

Top Venues

Publications

Steffen Rendle
Efficient Optimization of Sparse User Encoder Recommenders. Trans. Recomm. Syst. 2 (3) (2024)
Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang
Private Learning with Public Features. AISTATS (2024)
Shib Sankar Dasgupta, Andrew McCallum, Steffen Rendle, Li Zhang
Answering Compositional Queries with Set-Theoretic Embeddings. CoRR (2023)
Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang
Private Learning with Public Features. CoRR (2023)
Steffen Rendle, Walid Krichene, Li Zhang, Yehuda Koren
Revisiting the Performance of iALS on Item Recommendation Benchmarks. RecSys (2022)
Walid Krichene, Steffen Rendle
On sampled metrics for item recommendation. Commun. ACM 65 (7) (2022)
Steve Chien, Prateek Jain, Walid Krichene, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang
Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates. ICML (2021)
Steffen Rendle
Item Recommendation from Implicit Feedback. CoRR (2021)
Steve Chien, Prateek Jain, Walid Krichene, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang
Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates. CoRR (2021)
Walid Krichene, Steffen Rendle
On Sampled Metrics for Item Recommendation (Extended Abstract). IJCAI (2021)
Steffen Rendle, Walid Krichene, Li Zhang, Yehuda Koren
Revisiting the Performance of iALS on Item Recommendation Benchmarks. CoRR (2021)
Harsh Mehta, Steffen Rendle, Walid Krichene, Li Zhang
ALX: Large Scale Matrix Factorization on TPUs. CoRR (2021)
Steffen Rendle, Walid Krichene, Li Zhang, Yehuda Koren
iALS++: Speeding up Matrix Factorization with Subspace Optimization. CoRR (2021)
Weiwei Kong, Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang
Rankmax: An Adaptive Projection Alternative to the Softmax Function. NeurIPS (2020)
Tao Wu, Ellie Ka In Chio, Heng-Tze Cheng, Yu Du, Steffen Rendle, Dima Kuzmin, Ritesh Agarwal, Li Zhang, John R. Anderson, Sarvjeet Singh, Tushar Chandra, Ed H. Chi, Wen Li, Ankit Kumar, Xiang Ma, Alex Soares, Nitin Jindal, Pei Cao
Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval. CoRR (2020)
Tao Wu, Ellie Ka In Chio, Heng-Tze Cheng, Yu Du, Steffen Rendle, Dima Kuzmin, Ritesh Agarwal, Li Zhang, John R. Anderson, Sarvjeet Singh, Tushar Chandra, Ed H. Chi, Wen Li, Ankit Kumar, Xiang Ma, Alex Soares, Nitin Jindal, Pei Cao
Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval. CIKM (2020)
Steffen Rendle, Walid Krichene, Li Zhang, John R. Anderson
Neural Collaborative Filtering vs. Matrix Factorization Revisited. RecSys (2020)
Steffen Rendle, Walid Krichene, Li Zhang, John R. Anderson
Neural Collaborative Filtering vs. Matrix Factorization Revisited. CoRR (2020)
Walid Krichene, Steffen Rendle
On Sampled Metrics for Item Recommendation. KDD (2020)
John R. Anderson, Qingqing Huang, Walid Krichene, Steffen Rendle, Li Zhang
Superbloom: Bloom filter meets Transformer. CoRR (2020)
Steffen Rendle
Evaluation Metrics for Item Recommendation under Sampling. CoRR (2019)
Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang, Xinyang Yi, Lichan Hong, Ed H. Chi, John R. Anderson
Efficient Training on Very Large Corpora via Gramian Estimation. ICLR (Poster) (2019)
Steffen Rendle, Li Zhang, Yehuda Koren
On the Difficulty of Evaluating Baselines: A Study on Recommender Systems. CoRR (2019)
Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang, Xinyang Yi, Lichan Hong, Ed H. Chi, John R. Anderson
Efficient Training on Very Large Corpora via Gramian Estimation. CoRR (2018)
Guy Blanc, Steffen Rendle
Adaptive Sampled Softmax with Kernel Based Sampling. ICML (2018)
Immanuel Bayer, Uwe Nagel, Steffen Rendle
Graph Based Relational Features for Collective Classification. CoRR (2017)
Immanuel Bayer, Xiangnan He, Bhargav Kanagal, Steffen Rendle
A Generic Coordinate Descent Framework for Learning from Implicit Feedback. WWW (2017)
Guy Blanc, Steffen Rendle
Adaptive Sampled Softmax with Kernel Based Sampling. CoRR (2017)
Steffen Rendle, Dennis Fetterly, Eugene J. Shekita, Bor-Yiing Su
Robust Large-Scale Machine Learning in the Cloud. KDD (2016)
Immanuel Bayer, Xiangnan He, Bhargav Kanagal, Steffen Rendle
A Generic Coordinate Descent Framework for Learning from Implicit Feedback. CoRR (2016)
Immanuel Bayer, Uwe Nagel, Steffen Rendle
Graph Based Relational Features for Collective Classification. PAKDD (2) (2015)
Steffen Rendle, Christoph Freudenthaler
Improving pairwise learning for item recommendation from implicit feedback. WSDM (2014)
Steffen Rendle
Scaling Factorization Machines to Relational Data. Proc. VLDB Endow. 6 (5) (2013)
Thierry Silbermann, Immanuel Bayer, Steffen Rendle
Sample selection for MCMC-based recommender systems. RecSys (2013)
Steffen Rendle
Learning recommender systems with adaptive regularization. WSDM (2012)
Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Lars Schmidt-Thieme
BPR: Bayesian Personalized Ranking from Implicit Feedback CoRR (2012)
Lucas Drumond, Steffen Rendle, Lars Schmidt-Thieme
Predicting RDF triples in incomplete knowledge bases with tensor factorization. SAC (2012)
Steffen Rendle
Factorization Machines with libFM. ACM Trans. Intell. Syst. Technol. 3 (3) (2012)
Zeno Gantner, Steffen Rendle, Christoph Freudenthaler, Lars Schmidt-Thieme
MyMediaLite: a free recommender system library. RecSys (2011)
Ulrik Brandes, Jürgen Lerner, Bobo Nick, Steffen Rendle
Network effects on interest rates in online social lending. GI-Jahrestagung (2011)
Steffen Rendle, Zeno Gantner, Christoph Freudenthaler, Lars Schmidt-Thieme
Fast context-aware recommendations with factorization machines. SIGIR (2011)
Steffen Rendle, Christoph Freudenthaler, Lars Schmidt-Thieme
Factorizing personalized Markov chains for next-basket recommendation. WWW (2010)
Zeno Gantner, Lucas Drumond, Christoph Freudenthaler, Steffen Rendle, Lars Schmidt-Thieme
Learning Attribute-to-Feature Mappings for Cold-Start Recommendations. ICDM (2010)
Steffen Rendle
Factorization Machines. ICDM (2010)
Steffen Rendle, Lars Schmidt-Thieme
Pairwise interaction tensor factorization for personalized tag recommendation. WSDM (2010)
Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Lars Schmidt-Thieme
BPR: Bayesian Personalized Ranking from Implicit Feedback. UAI (2009)
Steffen Rendle, Christine Preisach, Lars Schmidt-Thieme
Learning to Extract Relations for Relational Classification. PAKDD (2009)
Zeno Gantner, Christoph Freudenthaler, Steffen Rendle, Lars Schmidt-Thieme
Optimal Ranking for Video Recommendation. UCMedia (2009)
Steffen Rendle, Lars Schmidt-Thieme
Factor Models for Tag Recommendation in BibSonomy. DC@PKDD/ECML (2009)
Steffen Rendle, Leandro Balby Marinho, Alexandros Nanopoulos, Lars Schmidt-Thieme
Learning optimal ranking with tensor factorization for tag recommendation. KDD (2009)
Steffen Rendle, Lars Schmidt-Thieme
Online-updating regularized kernel matrix factorization models for large-scale recommender systems. RecSys (2008)
Steffen Rendle, Lars Schmidt-Thieme
Active Learning of Equivalence Relations by Minimizing the Expected Loss Using Constraint Inference. ICDM (2008)
Steffen Rendle, Lars Schmidt-Thieme
Scaling Record Linkage to Non-uniform Distributed Class Sizes. PAKDD (2008)
Steffen Rendle, Lars Schmidt-Thieme
Information Integration of Partially Labeled Data. GfKl (2007)
Steffen Rendle, Lars Schmidt-Thieme
Object Identification with Constraints. ICDM (2006)
Jochen Fischer, Zeno Gantner, Steffen Rendle, Manuel Stritt, Lars Schmidt-Thieme
Ideas and Improvements for Semantic Wikis. ESWC (2006)