Steffen Rendle

According to our database, Steffen Rendle authored at least 51 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Efficient Optimization of Sparse User Encoder Recommenders.

Steffen Rendle

Trans. Recomm. Syst., September, 2024

Improved Estimation of Ranks for Learning Item Recommenders with Negative Sampling.

Anushya Subbiah, Steffen Rendle, Vikram Aggarwal

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Private Learning with Public Features.

Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Training Differentially Private Ad Prediction Models With Semi-Sensitive Features.

Lynn Chua, Qiliang Cui, Badih Ghazi, Charlie Harrison, Pritish Kamath, Walid Krichene, Ravi Kumar, Pasin Manurangsi, Nicolas Mayoraz, Hema Venkata Krishna Giri Narra, Steffen Rendle, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang

Proceedings of the Workshop on Data Mining for Online Advertising (AdKDD 2024) co-located with the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024), 2024

2023

Answering Compositional Queries with Set-Theoretic Embeddings.

Shib Sankar Dasgupta, Andrew McCallum, Steffen Rendle, Li Zhang

CoRR, 2023

2022

Item Recommendation from Implicit Feedback.

Steffen Rendle

Proceedings of the Recommender Systems Handbook, 2022

Advances in Collaborative Filtering.

Yehuda Koren, Steffen Rendle, Robert M. Bell

Proceedings of the Recommender Systems Handbook, 2022

On sampled metrics for item recommendation.

Walid Krichene, Steffen Rendle

Commun. ACM, 2022

Revisiting the Performance of iALS on Item Recommendation Benchmarks.

Steffen Rendle, Walid Krichene, Li Zhang, Yehuda Koren

Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

2021

ALX: Large Scale Matrix Factorization on TPUs.

Harsh Mehta, Steffen Rendle, Walid Krichene, Li Zhang

CoRR, 2021

iALS++: Speeding up Matrix Factorization with Subspace Optimization.

Steffen Rendle, Walid Krichene, Li Zhang, Yehuda Koren

CoRR, 2021

Item Recommendation from Implicit Feedback.

Steffen Rendle

CoRR, 2021

On Sampled Metrics for Item Recommendation (Extended Abstract).

Walid Krichene, Steffen Rendle

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates.

Steve Chien, Prateek Jain, Walid Krichene, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Superbloom: Bloom filter meets Transformer.

John R. Anderson, Qingqing Huang, Walid Krichene, Steffen Rendle, Li Zhang

CoRR, 2020

Neural Collaborative Filtering vs. Matrix Factorization Revisited.

Steffen Rendle, Walid Krichene, Li Zhang, John R. Anderson

Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

Rankmax: An Adaptive Projection Alternative to the Softmax Function.

Weiwei Kong, Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

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, John R. Anderson, Sarvjeet Singh, Tushar Chandra, Ed H. Chi, Wen Li, Ankit Kumar, Xiang Ma, Alex Soares, Nitin Jindal, Pei Cao

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019

Evaluation Metrics for Item Recommendation under Sampling.

Steffen Rendle

CoRR, 2019

On the Difficulty of Evaluating Baselines: A Study on Recommender Systems.

Steffen Rendle, Li Zhang, Yehuda Koren

CoRR, 2019

Efficient Training on Very Large Corpora via Gramian Estimation.

Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang, Xinyang Yi, Lichan Hong, Ed H. Chi, John R. Anderson

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Adaptive Sampled Softmax with Kernel Based Sampling.

Guy Blanc, Steffen Rendle

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

A Generic Coordinate Descent Framework for Learning from Implicit Feedback.

Immanuel Bayer, Xiangnan He, Bhargav Kanagal, Steffen Rendle

Proceedings of the 26th International Conference on World Wide Web, 2017

2016

Robust Large-Scale Machine Learning in the Cloud.

Steffen Rendle, Dennis Fetterly, Eugene J. Shekita, Bor-Yiing Su

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

2015

Graph Based Relational Features for Collective Classification.

Immanuel Bayer, Uwe Nagel, Steffen Rendle

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2015

2014

Improving pairwise learning for item recommendation from implicit feedback.

Steffen Rendle, Christoph Freudenthaler

Proceedings of the Seventh ACM International Conference on Web Search and Data Mining, 2014

2013

Scaling Factorization Machines to Relational Data.

Steffen Rendle

Proc. VLDB Endow., 2013

Sample selection for MCMC-based recommender systems.

Thierry Silbermann, Immanuel Bayer, Steffen Rendle

Proceedings of the Seventh ACM Conference on Recommender Systems, 2013

2012

Factorization Machines with libFM.

Steffen Rendle

ACM Trans. Intell. Syst. Technol., 2012

Learning recommender systems with adaptive regularization.

Steffen Rendle

Proceedings of the Fifth International Conference on Web Search and Web Data Mining, 2012

Predicting RDF triples in incomplete knowledge bases with tensor factorization.

Lucas Drumond, Steffen Rendle, Lars Schmidt-Thieme

Proceedings of the ACM Symposium on Applied Computing, 2012

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 Briefs in Electrical and Computer Engineering, Springer, ISBN: 978-1-4614-1894-8, 2012

2011

Context-Aware Ranking with Factorization Models

Steffen Rendle

Studies in Computational Intelligence 330, Springer, ISBN: 978-3-642-16897-0, 2011

Fast context-aware recommendations with factorization machines.

Steffen Rendle, Zeno Gantner, Christoph Freudenthaler, Lars Schmidt-Thieme

Proceedings of the Proceeding of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2011

MyMediaLite: a free recommender system library.

Zeno Gantner, Steffen Rendle, Christoph Freudenthaler, Lars Schmidt-Thieme

Proceedings of the 2011 ACM Conference on Recommender Systems, 2011

Network effects on interest rates in online social lending.

Ulrik Brandes, Jürgen Lerner, Bobo Nick, Steffen Rendle

Proceedings of the 41. Jahrestagung der Gesellschaft für Informatik, 2011

2010

Factorizing personalized Markov chains for next-basket recommendation.

Steffen Rendle, Christoph Freudenthaler, Lars Schmidt-Thieme

Proceedings of the 19th International Conference on World Wide Web, 2010

Pairwise interaction tensor factorization for personalized tag recommendation.

Steffen Rendle, Lars Schmidt-Thieme

Proceedings of the Third International Conference on Web Search and Web Data Mining, 2010

Factorization Machines.

Steffen Rendle

Proceedings of the ICDM 2010, 2010

Learning Attribute-to-Feature Mappings for Cold-Start Recommendations.

Zeno Gantner, Lucas Drumond, Christoph Freudenthaler, Steffen Rendle, Lars Schmidt-Thieme

Proceedings of the ICDM 2010, 2010

2009

Optimal Ranking for Video Recommendation.

Zeno Gantner, Christoph Freudenthaler, Steffen Rendle, Lars Schmidt-Thieme

Proceedings of the User Centric Media - First International Conference, 2009

BPR: Bayesian Personalized Ranking from Implicit Feedback.

Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Lars Schmidt-Thieme

Proceedings of the UAI 2009, 2009

Factor Models for Tag Recommendation in BibSonomy.

Steffen Rendle, Lars Schmidt-Thieme

Proceedings of ECML PKDD (The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases) Discovery Challenge 2009, 2009

Learning to Extract Relations for Relational Classification.

Steffen Rendle, Christine Preisach, Lars Schmidt-Thieme

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2009

Learning optimal ranking with tensor factorization for tag recommendation.

Steffen Rendle, Leandro Balby Marinho, Alexandros Nanopoulos, Lars Schmidt-Thieme

Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

2008

Online-updating regularized kernel matrix factorization models for large-scale recommender systems.

Steffen Rendle, Lars Schmidt-Thieme

Proceedings of the 2008 ACM Conference on Recommender Systems, 2008

Scaling Record Linkage to Non-uniform Distributed Class Sizes.

Steffen Rendle, Lars Schmidt-Thieme

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2008

Active Learning of Equivalence Relations by Minimizing the Expected Loss Using Constraint Inference.

Steffen Rendle, Lars Schmidt-Thieme

Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

2007

Information Integration of Partially Labeled Data.

Steffen Rendle, Lars Schmidt-Thieme

Proceedings of the Data Analysis, Machine Learning and Applications, 2007

2006

Object Identification with Constraints.

Steffen Rendle, Lars Schmidt-Thieme

Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 2006), 2006

Ideas and Improvements for Semantic Wikis.

Jochen Fischer, Zeno Gantner, Steffen Rendle, Manuel Stritt, Lars Schmidt-Thieme

Proceedings of the Semantic Web: Research and Applications, 2006