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Rolf Jagerman
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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
572019
When people change their mind: Off-policy evaluation in non-stationary recommendation environments
R Jagerman, I Markov, M de Rijke
Proceedings of the twelfth ACM international conference on web search and …, 2019
482019
Opensearch: lessons learned from an online evaluation campaign
R Jagerman, K Balog, MD Rijke
Journal of Data and Information Quality (JDIQ) 10 (3), 1-15, 2018
242018
Learning to rank in theory and practice: from gradient boosting to neural networks and unbiased learning
C Lucchese, FM Nardini, RK Pasumarthi, S Bruch, M Bendersky, X Wang, ...
Proceedings of the 42nd International ACM SIGIR Conference on Research and …, 2019
19*2019
Safe exploration for optimizing contextual bandits
R Jagerman, I Markov, MD Rijke
ACM Transactions on Information Systems (TOIS) 38 (3), 1-23, 2020
152020
Computing Web-scale Topic Models using an Asynchronous Parameter Server
R Jagerman, C Eickhoff, M de Rijke
Proceedings of the 40th International ACM SIGIR Conference on Research and …, 2017
152017
The fifteen year struggle of decentralizing privacy-enhancing technology
R Jagerman, W Sabee, L Versluis, M de Vos, J Pouwelse
arXiv preprint arXiv:1404.4818, 2014
112014
Modeling Label Ambiguity for Neural List-Wise Learning to Rank
R Jagerman, J Kiseleva, M de Rijke
2nd International Workshop on Neural Information Retrieval (Neu-IR), 2017
102017
Accelerated Convergence for Counterfactual Learning to Rank
R Jagerman, M de Rijke
Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020
82020
Rax: Composable learning-to-rank using JAX
R Jagerman, X Wang, H Zhuang, Z Qin, M Bendersky, M Najork
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
62022
Bootstrapping recommendations at chrome web store
Z Qin, H Zhuang, R Jagerman, X Qian, P Hu, DC Chen, X Wang, ...
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
62021
Rankt5: Fine-tuning T5 for text ranking with ranking losses
H Zhuang, Z Qin, R Jagerman, K Hui, J Ma, J Lu, J Ni, X Wang, ...
arXiv preprint arXiv:2210.10634, 2022
52022
Query-level Ranker Specialization
R Jagerman, H Oosterhuis, M de Rijke
1st International Workshop on LEARning Next gEneration Rankers (LEARNER), 2017
42017
On optimizing top-k metrics for neural ranking models
R Jagerman, Z Qin, X Wang, M Bendersky, M Najork
32022
Overview of TREC OpenSearch 2017.
R Jagerman, K Balog, P Schaer, J Schaible, N Tavakolpoursaleh, ...
TREC, 2017
32017
Improving Cloud Storage Search with User Activity.
R Jagerman, W Kong, RK Pasumarthi, Z Qin, M Bendersky, M Najork
WSDM, 508-516, 2021
12021
Modeling label ambiguity for listwise neural learning to rank
R Jagerman, J Kiseleva, M de Rijke
Neu-IR, 2017
12017
Regression Compatible Listwise Objectives for Calibrated Ranking
A Bai, R Jagerman, Z Qin, P Kar, BR Lin, X Wang, M Bendersky, M Najork
arXiv preprint arXiv:2211.01494, 2022
2022
Efficient, safe and adaptive learning from user interactions
R Lagerman
Universiteit van Amsterdam, 2020
2020
A Directional Diffusion Algorithm for Inpainting
J Deriu, R Jagerman, KE Tsay
arXiv preprint arXiv:1511.03464, 2015
2015
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Articles 1–20