| 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 | 86 | 2016 |
| Differentiable unbiased online learning to rank H Oosterhuis, M de Rijke Proceedings of the 27th ACM international conference on information and …, 2018 | 59 | 2018 |
| 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 | 57 | 2019 |
| 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 | 55 | 2020 |
| 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 | 42 | 2022 |
| 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 | 35 | 2020 |
| 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 | 34 | 2015 |
| 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 | 32 | 2021 |
| Probabilistic multileave gradient descent H Oosterhuis, A Schuth, M de Rijke Advances in Information Retrieval: 38th European Conference on IR Research …, 2016 | 31 | 2016 |
| 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 | 28 | 2018 |
| The Potential of Learned Index Structures for Index Compression H Oosterhuis, JS Culpepper, M de Rijke Australasian Document Computing Symposium (ADCS) 23, 2018 | 27 | 2018 |
| 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 | 26 | 2020 |
| 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 | 25 | 2021 |
| 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 | 23 | 2017 |
| 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 | 21 | 2017 |
| Optimizing ranking models in an online setting H Oosterhuis, M de Rijke Advances in Information Retrieval: 41st European Conference on IR Research …, 2019 | 15 | 2019 |
| Semantic video trailers H Oosterhuis, S Ravi, M Bendersky ICML 2016 Workshop on Multi-View Representation Learning, 2016 | 13 | 2016 |
| Taking the counterfactual online: Efficient and unbiased online evaluation for ranking H Oosterhuis, M de Rijke Proceedings of the 2020 ACM SIGIR on international conference on theory of …, 2020 | 12 | 2020 |
| 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 | 12 | 2020 |
| 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 | 11 | 2021 |
Maarten de RijkeUniversity of Amsterdam & ICAIVerified email at uva.nl
