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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
1002016
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
792020
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
752019
Differentiable unbiased online learning to rank
H Oosterhuis, M de Rijke
Proceedings of the 27th ACM international conference on information and†…, 2018
752018
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
632022
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
512021
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
502020
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
452020
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
432021
Probabilistic multileave for online retrieval evaluation
A Schuth, RJ Bruintjes, F BuŁttner, J van Doorn, C Groenland, ...
Proceedings of the 38th international ACM SIGIR conference on research and†…, 2015
362015
Probabilistic multileave gradient descent
H Oosterhuis, A Schuth, M de Rijke
Advances in Information Retrieval: 38th European Conference on IR Research†…, 2016
322016
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
292018
The Potential of Learned Index Structures for Index Compression
H Oosterhuis, JS Culpepper, M de Rijke
Australasian Document Computing Symposium (ADCS) 23, 2018
282018
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
272017
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
232017
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
212022
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
192020
Doubly-Robust Estimation for Correcting Position-Bias in Click Feedback for Unbiased Learning to Rank
H Oosterhuis
ACM Transactions on Information Systems, 2023
18*2023
Optimizing ranking models in an online setting
H Oosterhuis, M de Rijke
Advances in Information Retrieval: 41st European Conference on IR Research†…, 2019
182019
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
172021
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