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Fairness in Ranking under Uncertainty


Jul 14, 2021
Ashudeep Singh, David Kempe, Thorsten Joachims

* Preprint under submission. 19 pages, 4 figures 

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Optimizing Rankings for Recommendation in Matching Markets


Jun 03, 2021
Yi Su, Magd Bayoumi, Thorsten Joachims


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Fairness of Exposure in Stochastic Bandits


Mar 03, 2021
Lequn Wang, Yiwei Bai, Wen Sun, Thorsten Joachims


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Fairness and Diversity for Rankings in Two-Sided Markets


Oct 04, 2020
Lequn Wang, Thorsten Joachims


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Content-based Music Similarity with Triplet Networks


Aug 11, 2020
Joseph Cleveland, Derek Cheng, Michael Zhou, Thorsten Joachims, Douglass Turnbull


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Off-policy Bandits with Deficient Support


Jun 16, 2020
Noveen Sachdeva, Yi Su, Thorsten Joachims

* 11 pages, 6 figures. Accepted for publication at KDD '20 (Research track) 

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Controlling Fairness and Bias in Dynamic Learning-to-Rank


May 29, 2020
Marco Morik, Ashudeep Singh, Jessica Hong, Thorsten Joachims

* First two authors contributed equally. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval 2020 

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MOReL : Model-Based Offline Reinforcement Learning


May 12, 2020
Rahul Kidambi, Aravind Rajeswaran, Praneeth Netrapalli, Thorsten Joachims

* First two authors contributed equally. 18 pages of main text. 2 sections of appendix 

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Fair Learning-to-Rank from Implicit Feedback


Nov 19, 2019
Himank Yadav, Zhengxiao Du, Thorsten Joachims


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Policy Learning for Fairness in Ranking


Feb 11, 2019
Ashudeep Singh, Thorsten Joachims


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CAB: Continuous Adaptive Blending Estimator for Policy Evaluation and Learning


Nov 19, 2018
Yi Su, Lequn Wang, Michele Santacatterina, Thorsten Joachims


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Counterfactual Learning-to-Rank for Additive Metrics and Deep Models


Jun 22, 2018
Aman Agarwal, Ivan Zaitsev, Thorsten Joachims


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Consistent Position Bias Estimation without Online Interventions for Learning-to-Rank


Jun 09, 2018
Aman Agarwal, Ivan Zaitsev, Thorsten Joachims


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Effective Evaluation using Logged Bandit Feedback from Multiple Loggers


Jun 26, 2017
Aman Agarwal, Soumya Basu, Tobias Schnabel, Thorsten Joachims

* KDD 2018 

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Large-scale Validation of Counterfactual Learning Methods: A Test-Bed


Jun 25, 2017
Damien Lefortier, Adith Swaminathan, Xiaotao Gu, Thorsten Joachims, Maarten de Rijke

* 10 pages, What If workshop NIPS 2016 

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Unbiased Learning-to-Rank with Biased Feedback


Aug 16, 2016
Thorsten Joachims, Adith Swaminathan, Tobias Schnabel


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Unbounded Human Learning: Optimal Scheduling for Spaced Repetition


Jun 08, 2016
Siddharth Reddy, Igor Labutov, Siddhartha Banerjee, Thorsten Joachims

* Accepted to the ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2016 

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Recommendations as Treatments: Debiasing Learning and Evaluation


May 27, 2016
Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, Thorsten Joachims

* 10 pages in ICML 2016 

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Unbiased Comparative Evaluation of Ranking Functions


Apr 25, 2016
Tobias Schnabel, Adith Swaminathan, Peter Frazier, Thorsten Joachims

* Under review; 10 pages 

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Latent Skill Embedding for Personalized Lesson Sequence Recommendation


Feb 23, 2016
Siddharth Reddy, Igor Labutov, Thorsten Joachims

* Under review by the ACM SIGKDD Conference on Knowledge Discovery and Data Mining 

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Using Shortlists to Support Decision Making and Improve Recommender System Performance


Feb 08, 2016
Tobias Schnabel, Paul N. Bennett, Susan T. Dumais, Thorsten Joachims

* 11 pages in WWW 2016 

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Learning Preferences for Manipulation Tasks from Online Coactive Feedback


Jan 05, 2016
Ashesh Jain, Shikhar Sharma, Thorsten Joachims, Ashutosh Saxena

* IJRR accepted (Learning preferences over trajectories from coactive feedback) 

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Counterfactual Risk Minimization: Learning from Logged Bandit Feedback


May 20, 2015
Adith Swaminathan, Thorsten Joachims

* 10 pages 

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Reducing Dueling Bandits to Cardinal Bandits


May 14, 2014
Nir Ailon, Thorsten Joachims, Zohar Karnin


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Methods for Ordinal Peer Grading


Apr 14, 2014
Karthik Raman, Thorsten Joachims

* Submitted to KDD 2014 

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Learning Trajectory Preferences for Manipulators via Iterative Improvement


Nov 05, 2013
Ashesh Jain, Brian Wojcik, Thorsten Joachims, Ashutosh Saxena

* 9 pages. To appear in NIPS 2013 

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Structured learning of sum-of-submodular higher order energy functions


Oct 01, 2013
Alexander Fix, Thorsten Joachims, Sam Park, Ramin Zabih


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Contextually Guided Semantic Labeling and Search for 3D Point Clouds


Sep 05, 2012
Abhishek Anand, Hema Swetha Koppula, Thorsten Joachims, Ashutosh Saxena

* arXiv admin note: substantial text overlap with arXiv:1106.5551 

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Unstructuring User Preferences: Efficient Non-Parametric Utility Revelation


Jul 04, 2012
Carmel Domshlak, Thorsten Joachims

* Appears in Proceedings of the Twenty-First Conference on Uncertainty in Artificial Intelligence (UAI2005) 

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Online Structured Prediction via Coactive Learning


Jun 27, 2012
Pannaga Shivaswamy, Thorsten Joachims


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