Steffen Rendle

66 papers A* 14A 12B 3Misc 1Journal 25Unranked 7

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Efficient Hyperparameter Search for Non-Stationary Model Training. CoRR Berivan Isik, Matthew Fahrbach, Dima Kuzmin, Nicolas Mayoraz, Emil Praun, Steffen Rendle, Raghavendra Vasudeva
2025	J	`jnl`	Efficient Item ID Generation for Large-Scale LLM-based Recommendation. CoRR Anushya Subbiah, Vikram Aggarwal, James Pine, Steffen Rendle, Krishna Sayana, Kun Su
2025	J	`jnl`	Successive Halving with Learning Curve Prediction via Latent Kronecker Gaussian Processes. CoRR Jihao Andreas Lin, Nicolas Mayoraz, Steffen Rendle, Dima Kuzmin, Emil Praun, Berivan Isik
2024	J	`jnl`	Efficient Optimization of Sparse User Encoder Recommenders. Trans. Recomm. Syst. Steffen Rendle
2024	A	`conf`	Improved Estimation of Ranks for Learning Item Recommenders with Negative Sampling. CIKM Anushya Subbiah, Steffen Rendle, Vikram Aggarwal
2024	J	`jnl`	Improved Estimation of Ranks for Learning Item Recommenders with Negative Sampling. CoRR Anushya Subbiah, Steffen Rendle, Vikram Aggarwal
2024	A	`conf`	Private Learning with Public Features. AISTATS Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang
2024	—	`conf`	Training Differentially Private Ad Prediction Models With Semi-Sensitive Features. AdKDD@KDD 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
2023	J	`jnl`	Answering Compositional Queries with Set-Theoretic Embeddings. CoRR Shib Sankar Dasgupta, Andrew McCallum, Steffen Rendle, Li Zhang
2023	J	`jnl`	Private Learning with Public Features. CoRR Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang
2022	—	`ch.`	Advances in Collaborative Filtering. Recommender Systems Handbook Yehuda Koren, Steffen Rendle, Robert M. Bell
2022	—	`ch.`	Item Recommendation from Implicit Feedback. Recommender Systems Handbook Steffen Rendle
2022	J	`jnl`	On sampled metrics for item recommendation. Commun. ACM Walid Krichene, Steffen Rendle
2022	A	`conf`	Revisiting the Performance of iALS on Item Recommendation Benchmarks. RecSys Steffen Rendle, Walid Krichene, Li Zhang, Yehuda Koren
2021	J	`jnl`	ALX: Large Scale Matrix Factorization on TPUs. CoRR Harsh Mehta, Steffen Rendle, Walid Krichene, Li Zhang
2021	J	`jnl`	Item Recommendation from Implicit Feedback. CoRR Steffen Rendle
2021	A*	`conf`	On Sampled Metrics for Item Recommendation (Extended Abstract). IJCAI Walid Krichene, Steffen Rendle
2021	A*	`conf`	Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates. ICML Steve Chien, Prateek Jain, Walid Krichene, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang
2021	J	`jnl`	Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates. CoRR Steve Chien, Prateek Jain, Walid Krichene, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang
2021	J	`jnl`	Revisiting the Performance of iALS on Item Recommendation Benchmarks. CoRR Steffen Rendle, Walid Krichene, Li Zhang, Yehuda Koren
2021	J	`jnl`	iALS++: Speeding up Matrix Factorization with Subspace Optimization. CoRR Steffen Rendle, Walid Krichene, Li Zhang, Yehuda Koren
2020	A	`conf`	Neural Collaborative Filtering vs. Matrix Factorization Revisited. RecSys Steffen Rendle, Walid Krichene, Li Zhang, John R. Anderson
2020	J	`jnl`	Neural Collaborative Filtering vs. Matrix Factorization Revisited. CoRR Steffen Rendle, Walid Krichene, Li Zhang, John R. Anderson
2020	A*	`conf`	On Sampled Metrics for Item Recommendation. KDD Walid Krichene, Steffen Rendle
2020	A*	`conf`	Rankmax: An Adaptive Projection Alternative to the Softmax Function. NeurIPS Weiwei Kong, Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang
2020	J	`jnl`	Superbloom: Bloom filter meets Transformer. CoRR John R. Anderson, Qingqing Huang, Walid Krichene, Steffen Rendle, Li Zhang
2020	A	`conf`	Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval. CIKM 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
2020	J	`jnl`	Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval. CoRR 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
2019	—	`conf`	Efficient Training on Very Large Corpora via Gramian Estimation. ICLR (Poster) Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang, Xinyang Yi, Lichan Hong, Ed H. Chi, John R. Anderson
2019	J	`jnl`	Evaluation Metrics for Item Recommendation under Sampling. CoRR Steffen Rendle
2019	J	`jnl`	On the Difficulty of Evaluating Baselines: A Study on Recommender Systems. CoRR Steffen Rendle, Li Zhang, Yehuda Koren
2018	A*	`conf`	Adaptive Sampled Softmax with Kernel Based Sampling. ICML Guy Blanc, Steffen Rendle
2018	J	`jnl`	Efficient Training on Very Large Corpora via Gramian Estimation. CoRR Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang, Xinyang Yi, Lichan Hong, Ed H. Chi, John R. Anderson
2017	A*	`conf`	A Generic Coordinate Descent Framework for Learning from Implicit Feedback. WWW Immanuel Bayer, Xiangnan He, Bhargav Kanagal, Steffen Rendle
2017	J	`jnl`	Adaptive Sampled Softmax with Kernel Based Sampling. CoRR Guy Blanc, Steffen Rendle
2017	J	`jnl`	Graph Based Relational Features for Collective Classification. CoRR Immanuel Bayer, Uwe Nagel, Steffen Rendle
2016	J	`jnl`	A Generic Coordinate Descent Framework for Learning from Implicit Feedback. CoRR Immanuel Bayer, Xiangnan He, Bhargav Kanagal, Steffen Rendle
2016	A*	`conf`	Robust Large-Scale Machine Learning in the Cloud. KDD Steffen Rendle, Dennis Fetterly, Eugene J. Shekita, Bor-Yiing Su
2015	—	`conf`	Graph Based Relational Features for Collective Classification. PAKDD (2) Immanuel Bayer, Uwe Nagel, Steffen Rendle
2014	A	`conf`	Improving pairwise learning for item recommendation from implicit feedback. WSDM Steffen Rendle, Christoph Freudenthaler
2013	A	`conf`	Sample selection for MCMC-based recommender systems. RecSys Thierry Silbermann, Immanuel Bayer, Steffen Rendle
2013	J	`jnl`	Scaling Factorization Machines to Relational Data. Proc. VLDB Endow. Steffen Rendle
2012	J	`jnl`	BPR: Bayesian Personalized Ranking from Implicit Feedback CoRR Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Lars Schmidt-Thieme
2012	J	`jnl`	Factorization Machines with libFM. ACM Trans. Intell. Syst. Technol. Steffen Rendle
2012	A	`conf`	Learning recommender systems with adaptive regularization. WSDM Steffen Rendle
2012	Misc	`conf`	Predicting RDF triples in incomplete knowledge bases with tensor factorization. SAC Lucas Drumond, Steffen Rendle, Lars Schmidt-Thieme
2012	—	`book`	Recommender Systems for Social Tagging Systems. Leandro Balby Marinho, Andreas Hotho, Robert Jäschke, Alexandros Nanopoulos, Steffen Rendle, Lars Schmidt-Thieme, Gerd Stumme, Panagiotis Symeonidis
2011	—	`book`	Context-Aware Ranking with Factorization Models Steffen Rendle
2011	A*	`conf`	Fast context-aware recommendations with factorization machines. SIGIR Steffen Rendle, Zeno Gantner, Christoph Freudenthaler, Lars Schmidt-Thieme
2011	A	`conf`	MyMediaLite: a free recommender system library. RecSys Zeno Gantner, Steffen Rendle, Christoph Freudenthaler, Lars Schmidt-Thieme
2011	—	`conf`	Network effects on interest rates in online social lending. GI-Jahrestagung Ulrik Brandes, Jürgen Lerner, Bobo Nick, Steffen Rendle
2010	A*	`conf`	Factorization Machines. ICDM Steffen Rendle
2010	A*	`conf`	Factorizing personalized Markov chains for next-basket recommendation. WWW Steffen Rendle, Christoph Freudenthaler, Lars Schmidt-Thieme
2010	A*	`conf`	Learning Attribute-to-Feature Mappings for Cold-Start Recommendations. ICDM Zeno Gantner, Lucas Drumond, Christoph Freudenthaler, Steffen Rendle, Lars Schmidt-Thieme
2010	A	`conf`	Pairwise interaction tensor factorization for personalized tag recommendation. WSDM Steffen Rendle, Lars Schmidt-Thieme
2009	A	`conf`	BPR: Bayesian Personalized Ranking from Implicit Feedback. UAI Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Lars Schmidt-Thieme
2009	—	`conf`	Factor Models for Tag Recommendation in BibSonomy. DC@PKDD/ECML Steffen Rendle, Lars Schmidt-Thieme
2009	A*	`conf`	Learning optimal ranking with tensor factorization for tag recommendation. KDD Steffen Rendle, Leandro Balby Marinho, Alexandros Nanopoulos, Lars Schmidt-Thieme
2009	B	`conf`	Learning to Extract Relations for Relational Classification. PAKDD Steffen Rendle, Christine Preisach, Lars Schmidt-Thieme
2009	—	`conf`	Optimal Ranking for Video Recommendation. UCMedia Zeno Gantner, Christoph Freudenthaler, Steffen Rendle, Lars Schmidt-Thieme
2008	A*	`conf`	Active Learning of Equivalence Relations by Minimizing the Expected Loss Using Constraint Inference. ICDM Steffen Rendle, Lars Schmidt-Thieme
2008	A	`conf`	Online-updating regularized kernel matrix factorization models for large-scale recommender systems. RecSys Steffen Rendle, Lars Schmidt-Thieme
2008	B	`conf`	Scaling Record Linkage to Non-uniform Distributed Class Sizes. PAKDD Steffen Rendle, Lars Schmidt-Thieme
2007	—	`conf`	Information Integration of Partially Labeled Data. GfKl Steffen Rendle, Lars Schmidt-Thieme
2006	B	`conf`	Ideas and Improvements for Semantic Wikis. ESWC Jochen Fischer, Zeno Gantner, Steffen Rendle, Manuel Stritt, Lars Schmidt-Thieme
2006	A*	`conf`	Object Identification with Constraints. ICDM Steffen Rendle, Lars Schmidt-Thieme