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ORCIDSteffen Rendle
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2020 – today
- 2024
[j4]Steffen Rendle
:
Efficient Optimization of Sparse User Encoder Recommenders. Trans. Recomm. Syst. 2(3): 22:1-22:31 (2024)- [c35]Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang:
Private Learning with Public Features. AISTATS 2024: 4150-4158 - 2023
- [i17]Shib Sankar Dasgupta, Andrew McCallum, Steffen Rendle, Li Zhang:
Answering Compositional Queries with Set-Theoretic Embeddings. CoRR abs/2306.04133 (2023) - [i16]Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang:
Private Learning with Public Features. CoRR abs/2310.15454 (2023) - 2022
- [j3]Walid Krichene, Steffen Rendle:
On sampled metrics for item recommendation. Commun. ACM 65(7): 75-83 (2022) - [c34]Steffen Rendle, Walid Krichene, Li Zhang, Yehuda Koren:
Revisiting the Performance of iALS on Item Recommendation Benchmarks. RecSys 2022: 427-435 - [r2]Yehuda Koren, Steffen Rendle, Robert M. Bell:
Advances in Collaborative Filtering. Recommender Systems Handbook 2022: 91-142 - [r1]Steffen Rendle:
Item Recommendation from Implicit Feedback. Recommender Systems Handbook 2022: 143-171 - 2021
- [c33]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: 1877-1887 - [c32]Walid Krichene, Steffen Rendle:
On Sampled Metrics for Item Recommendation (Extended Abstract). IJCAI 2021: 4784-4788 - [i15]Steffen Rendle:
Item Recommendation from Implicit Feedback. CoRR abs/2101.08769 (2021) - [i14]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 abs/2107.09802 (2021) - [i13]Steffen Rendle, Walid Krichene, Li Zhang, Yehuda Koren:
Revisiting the Performance of iALS on Item Recommendation Benchmarks. CoRR abs/2110.14037 (2021) - [i12]Steffen Rendle, Walid Krichene, Li Zhang, Yehuda Koren:
iALS++: Speeding up Matrix Factorization with Subspace Optimization. CoRR abs/2110.14044 (2021) - [i11]Harsh Mehta, Steffen Rendle, Walid Krichene, Li Zhang:
ALX: Large Scale Matrix Factorization on TPUs. CoRR abs/2112.02194 (2021) - 2020
- [c31]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: 2821-2828 - [c30]Walid Krichene, Steffen Rendle:
On Sampled Metrics for Item Recommendation. KDD 2020: 1748-1757 - [c29]Weiwei Kong, Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang:
Rankmax: An Adaptive Projection Alternative to the Softmax Function. NeurIPS 2020 - [c28]Steffen Rendle, Walid Krichene, Li Zhang, John R. Anderson:
Neural Collaborative Filtering vs. Matrix Factorization Revisited. RecSys 2020: 240-248 - [i10]John R. Anderson, Qingqing Huang, Walid Krichene, Steffen Rendle, Li Zhang:
Superbloom: Bloom filter meets Transformer. CoRR abs/2002.04723 (2020) - [i9]Steffen Rendle, Walid Krichene, Li Zhang, John R. Anderson:
Neural Collaborative Filtering vs. Matrix Factorization Revisited. CoRR abs/2005.09683 (2020) - [i8]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 abs/2008.02930 (2020)
2010 – 2019
- 2019
- [c27]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 - [i7]Steffen Rendle, Li Zhang, Yehuda Koren:
On the Difficulty of Evaluating Baselines: A Study on Recommender Systems. CoRR abs/1905.01395 (2019) - [i6]Steffen Rendle:
Evaluation Metrics for Item Recommendation under Sampling. CoRR abs/1912.02263 (2019) - 2018
- [c26]Guy Blanc, Steffen Rendle:
Adaptive Sampled Softmax with Kernel Based Sampling. ICML 2018: 589-598 - [i5]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 abs/1807.07187 (2018) - 2017
- [c25]Immanuel Bayer, Xiangnan He, Bhargav Kanagal, Steffen Rendle:
A Generic Coordinate Descent Framework for Learning from Implicit Feedback. WWW 2017: 1341-1350 - [i4]Immanuel Bayer, Uwe Nagel, Steffen Rendle:
Graph Based Relational Features for Collective Classification. CoRR abs/1702.02817 (2017) - [i3]Guy Blanc, Steffen Rendle:
Adaptive Sampled Softmax with Kernel Based Sampling. CoRR abs/1712.00527 (2017) - 2016
- [c24]Steffen Rendle, Dennis Fetterly, Eugene J. Shekita, Bor-Yiing Su:
Robust Large-Scale Machine Learning in the Cloud. KDD 2016: 1125-1134 - [i2]Immanuel Bayer, Xiangnan He, Bhargav Kanagal, Steffen Rendle:
A Generic Coordinate Descent Framework for Learning from Implicit Feedback. CoRR abs/1611.04666 (2016) - 2015
- [c23]Immanuel Bayer, Uwe Nagel, Steffen Rendle:
Graph Based Relational Features for Collective Classification. PAKDD (2) 2015: 447-458 - 2014
- [c22]Steffen Rendle, Christoph Freudenthaler:
Improving pairwise learning for item recommendation from implicit feedback. WSDM 2014: 273-282 - 2013
- [j2]Steffen Rendle:
Scaling Factorization Machines to Relational Data. Proc. VLDB Endow. 6(5): 337-348 (2013) - [c21]Thierry Silbermann, Immanuel Bayer, Steffen Rendle:
Sample selection for MCMC-based recommender systems. RecSys 2013: 403-406 - 2012
- [b2]Leandro Balby Marinho, Andreas Hotho, Robert Jäschke, Alexandros Nanopoulos, Steffen Rendle, Lars Schmidt-Thieme, Gerd Stumme, Panagiotis Symeonidis:
Recommender Systems for Social Tagging Systems. Springer Briefs in Electrical and Computer Engineering, Springer 2012, ISBN 978-1-4614-1893-1, pp. i-ix, 1-111 - [j1]Steffen Rendle:
Factorization Machines with libFM. ACM Trans. Intell. Syst. Technol. 3(3): 57:1-57:22 (2012) - [c20]Lucas Drumond, Steffen Rendle, Lars Schmidt-Thieme:
Predicting RDF triples in incomplete knowledge bases with tensor factorization. SAC 2012: 326-331 - [c19]Steffen Rendle:
Learning recommender systems with adaptive regularization. WSDM 2012: 133-142 - [i1]Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Lars Schmidt-Thieme:
BPR: Bayesian Personalized Ranking from Implicit Feedback. CoRR abs/1205.2618 (2012) - 2011
- [b1]Steffen Rendle:
Context-Aware Ranking with Factorization Models. Studies in Computational Intelligence 330, Springer 2011, ISBN 978-3-642-16897-0, pp. 3-176 [contents] - [c18]Ulrik Brandes, Jürgen Lerner, Bobo Nick, Steffen Rendle:
Network effects on interest rates in online social lending. GI-Jahrestagung 2011: 429 - [c17]Zeno Gantner, Steffen Rendle, Christoph Freudenthaler, Lars Schmidt-Thieme:
MyMediaLite: a free recommender system library. RecSys 2011: 305-308 - [c16]Steffen Rendle, Zeno Gantner, Christoph Freudenthaler, Lars Schmidt-Thieme:
Fast context-aware recommendations with factorization machines. SIGIR 2011: 635-644 - 2010
- [c15]Zeno Gantner, Lucas Drumond, Christoph Freudenthaler, Steffen Rendle, Lars Schmidt-Thieme:
Learning Attribute-to-Feature Mappings for Cold-Start Recommendations. ICDM 2010: 176-185 - [c14]Steffen Rendle:
Factorization Machines. ICDM 2010: 995-1000 - [c13]Steffen Rendle, Lars Schmidt-Thieme:
Pairwise interaction tensor factorization for personalized tag recommendation. WSDM 2010: 81-90 - [c12]Steffen Rendle, Christoph Freudenthaler, Lars Schmidt-Thieme:
Factorizing personalized Markov chains for next-basket recommendation. WWW 2010: 811-820
2000 – 2009
- 2009
- [c11]Steffen Rendle, Leandro Balby Marinho, Alexandros Nanopoulos, Lars Schmidt-Thieme:
Learning optimal ranking with tensor factorization for tag recommendation. KDD 2009: 727-736 - [c10]Steffen Rendle, Christine Preisach, Lars Schmidt-Thieme:
Learning to Extract Relations for Relational Classification. PAKDD 2009: 1062-1071 - [c9]Steffen Rendle, Lars Schmidt-Thieme:
Factor Models for Tag Recommendation in BibSonomy. DC@PKDD/ECML 2009 - [c8]Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Lars Schmidt-Thieme:
BPR: Bayesian Personalized Ranking from Implicit Feedback. UAI 2009: 452-461 - [c7]Zeno Gantner, Christoph Freudenthaler, Steffen Rendle, Lars Schmidt-Thieme:
Optimal Ranking for Video Recommendation. UCMedia 2009: 255-258 - 2008
- [c6]Steffen Rendle, Lars Schmidt-Thieme:
Active Learning of Equivalence Relations by Minimizing the Expected Loss Using Constraint Inference. ICDM 2008: 1001-1006 - [c5]Steffen Rendle, Lars Schmidt-Thieme:
Scaling Record Linkage to Non-uniform Distributed Class Sizes. PAKDD 2008: 308-319 - [c4]Steffen Rendle, Lars Schmidt-Thieme:
Online-updating regularized kernel matrix factorization models for large-scale recommender systems. RecSys 2008: 251-258 - 2007
- [c3]Steffen Rendle, Lars Schmidt-Thieme:
Information Integration of Partially Labeled Data. GfKl 2007: 171-179 - 2006
- [c2]Jochen Fischer, Zeno Gantner, Steffen Rendle, Manuel Stritt, Lars Schmidt-Thieme:
Ideas and Improvements for Semantic Wikis. ESWC 2006: 650-663 - [c1]Steffen Rendle, Lars Schmidt-Thieme:
Object Identification with Constraints. ICDM 2006: 1026-1031
Coauthor Index
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last updated on 2024-07-29 21:31 CEST by the dblp team
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