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Harrie Oosterhuis
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Year
Multileave gradient descent for fast online learning to rank
A Schuth, H Oosterhuis, S Whiteson, M de Rijke
proceedings of the ninth ACM international conference on web search and data …, 2016
1102016
Keeping dataset biases out of the simulation: A debiased simulator for reinforcement learning based recommender systems
J Huang, H Oosterhuis, M De Rijke, H Van Hoof
Proceedings of the 14th ACM conference on recommender systems, 190-199, 2020
992020
FOCUS: Flexible optimizable counterfactual explanations for tree ensembles
A Lucic, H Oosterhuis, H Haned, M de Rijke
Proceedings of the AAAI Conference on Artificial Intelligence 36 (5), 5313-5322, 2022
91*2022
Differentiable unbiased online learning to rank
H Oosterhuis, M de Rijke
Proceedings of the 27th ACM international conference on information and …, 2018
872018
To Model or to Intervene: A Comparison of Counterfactual and Online Learning to Rank from User Interactions
R Jagerman, H Oosterhuis, M de Rijke
Proceedings of the 42nd International ACM SIGIR Conference on Research and …, 2019
792019
Computationally Efficient Optimization of Plackett-Luce Ranking Models for Relevance and Fairness
H Oosterhuis
Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021
682021
Policy-aware unbiased learning to rank for top-k rankings
H Oosterhuis, M de Rijke
Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020
672020
When inverse propensity scoring does not work: Affine corrections for unbiased learning to rank
A Vardasbi, H Oosterhuis, M de Rijke
Proceedings of the 29th ACM International Conference on Information …, 2020
652020
Unifying online and counterfactual learning to rank: A novel counterfactual estimator that effectively utilizes online interventions
H Oosterhuis, M de Rijke
Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021
582021
Probabilistic multileave for online retrieval evaluation
A Schuth, RJ Bruintjes, F Buüttner, J van Doorn, C Groenland, ...
Proceedings of the 38th international ACM SIGIR Conference on Research and …, 2015
372015
Doubly-Robust Estimation for Correcting Position-Bias in Click Feedback for Unbiased Learning to Rank
H Oosterhuis
ACM Transactions on Information Systems, 2023
35*2023
It Is Different When Items Are Older: Debiasing Recommendations When Selection Bias and User Preferences Are Dynamic
J Huang, H Oosterhuis, M de Rijke
Proceedings of the Fifteenth ACM International Conference on Web Search and …, 2022
352022
Probabilistic multileave gradient descent
H Oosterhuis, A Schuth, M de Rijke
Advances in Information Retrieval: 38th European Conference on IR Research …, 2016
332016
Ranking for Relevance and Display Preferences in Complex Presentation Layouts
H Oosterhuis, M de Rijke
SIGIR 2018: 41st international ACM SIGIR conference on Research and …, 2018
322018
Balancing Speed and Quality in Online Learning to Rank for Information Retrieval
H Oosterhuis, M de Rijke
CIKM '17 ACM Conference on Information and Knowledge Management, 277-286, 2017
292017
The Potential of Learned Index Structures for Index Compression
H Oosterhuis, JS Culpepper, M de Rijke
Australasian Document Computing Symposium (ADCS) 23, 2018
282018
Robust Generalization and Safe Query-Specialization in Counterfactual Learning to Rank
H Oosterhuis, M de Rijke
Proceedings of the Web Conference 2021, 158-170, 2021
252021
Sensitive and Scalable Online Evaluation with Theoretical Guarantees
H Oosterhuis, M de Rijke
CIKM '17 ACM Conference on Information and Knowledge Management, 77-86, 2017
242017
Learning from User Interactions with Rankings: A Unification of the Field
H Oosterhuis
University of Amsterdam, 2020
232020
Unbiased learning to rank: counterfactual and online approaches
H Oosterhuis, R Jagerman, M de Rijke
Companion Proceedings of the Web Conference 2020, 299-300, 2020
232020
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