Rolf Jagerman

According to our database, Rolf Jagerman authored at least 26 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Generate, Filter, and Fuse: Query Expansion via Multi-Step Keyword Generation for Zero-Shot Neural Rankers.

Minghan Li, Honglei Zhuang, Kai Hui, Zhen Qin, Jimmy Lin, Rolf Jagerman, Xuanhui Wang, Michael Bendersky

CoRR, 2023

Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting.

Zhen Qin, Rolf Jagerman, Kai Hui, Honglei Zhuang, Junru Wu, Jiaming Shen, Tianqi Liu, Jialu Liu, Donald Metzler, Xuanhui Wang, Michael Bendersky

CoRR, 2023

RD-Suite: A Benchmark for Ranking Distillation.

Zhen Qin, Rolf Jagerman, Rama Kumar Pasumarthi, Honglei Zhuang, He Zhang, Aijun Bai, Kai Hui, Le Yan, Xuanhui Wang

CoRR, 2023

Query Expansion by Prompting Large Language Models.

Rolf Jagerman, Honglei Zhuang, Zhen Qin, Xuanhui Wang, Michael Bendersky

CoRR, 2023

RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses.

Honglei Zhuang, Zhen Qin, Rolf Jagerman, Kai Hui, Ji Ma, Jing Lu, Jianmo Ni, Xuanhui Wang, Michael Bendersky

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

RD-Suite: A Benchmark for Ranking Distillation.

Zhen Qin, Rolf Jagerman, Rama Kumar Pasumarthi, Honglei Zhuang, He Zhang, Aijun Bai, Kai Hui, Le Yan, Xuanhui Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Regression Compatible Listwise Objectives for Calibrated Ranking with Binary Relevance.

Aijun Bai, Rolf Jagerman, Zhen Qin, Le Yan, Pratyush Kar, Bing-Rong Lin, Xuanhui Wang, Michael Bendersky, Marc Najork

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

Regression Compatible Listwise Objectives for Calibrated Ranking.

Aijun Bai, Rolf Jagerman, Zhen Qin, Pratyush Kar, Bing-Rong Lin, Xuanhui Wang, Michael Bendersky, Marc Najork

CoRR, 2022

On Optimizing Top-K Metrics for Neural Ranking Models.

Rolf Jagerman, Zhen Qin, Xuanhui Wang, Michael Bendersky, Marc Najork

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Rax: Composable Learning-to-Rank Using JAX.

Rolf Jagerman, Xuanhui Wang, Honglei Zhuang, Zhen Qin, Michael Bendersky, Marc Najork

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

Improving Cloud Storage Search with User Activity.

Rolf Jagerman, Weize Kong, Rama Kumar Pasumarthi, Zhen Qin, Michael Bendersky, Marc Najork

Proceedings of the WSDM '21, 2021

Bootstrapping Recommendations at Chrome Web Store.

Zhen Qin, Honglei Zhuang, Rolf Jagerman, Xinyu Qian, Po Hu, Dan Chary Chen, Xuanhui Wang, Michael Bendersky, Marc Najork

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020

Safe Exploration for Optimizing Contextual Bandits.

Rolf Jagerman, Ilya Markov, Maarten de Rijke

ACM Trans. Inf. Syst., 2020

Unbiased Learning to Rank: Counterfactual and Online Approaches.

Harrie Oosterhuis, Rolf Jagerman, Maarten de Rijke

Proceedings of the Companion of The 2020 Web Conference 2020, 2020

Accelerated Convergence for Counterfactual Learning to Rank.

Rolf Jagerman, Maarten de Rijke

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

2019

When People Change their Mind: Off-Policy Evaluation in Non-stationary Recommendation Environments.

Rolf Jagerman, Ilya Markov, Maarten de Rijke

Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019

Learning to Rank in Theory and Practice: From Gradient Boosting to Neural Networks and Unbiased Learning.

Claudio Lucchese, Franco Maria Nardini, Rama Kumar Pasumarthi, Sebastian Bruch, Michael Bendersky, Xuanhui Wang, Harrie Oosterhuis, Rolf Jagerman, Maarten de Rijke

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

To Model or to Intervene: A Comparison of Counterfactual and Online Learning to Rank from User Interactions.

Rolf Jagerman, Harrie Oosterhuis, Maarten de Rijke

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

2018

OpenSearch: Lessons Learned from an Online Evaluation Campaign.

Rolf Jagerman, Krisztian Balog, Maarten de Rijke

ACM J. Data Inf. Qual., 2018

2017

Modeling Label Ambiguity for Neural List-Wise Learning to Rank.

Rolf Jagerman, Julia Kiseleva, Maarten de Rijke

CoRR, 2017

Overview of TREC OpenSearch 2017.

Rolf Jagerman, Krisztian Balog, Philipp Schaer, Johann Schaible, Narges Tavakolpoursaleh, Maarten de Rijke

Proceedings of The Twenty-Sixth Text REtrieval Conference, 2017

Computing Web-scale Topic Models using an Asynchronous Parameter Server.

Rolf Jagerman, Carsten Eickhoff, Maarten de Rijke

Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017

Query-Level Ranker Specialization.

Rolf Jagerman, Harrie Oosterhuis, Maarten de Rijke

Proceedings of the 1st International Workshop on LEARning Next gEneration Rankers co-located with the 3rd ACM International Conference on the Theory of Information Retrieval (ICTIR 2017), 2017

2016

Web-scale Topic Models in Spark: An Asynchronous Parameter Server.

Rolf Jagerman, Carsten Eickhoff

CoRR, 2016

2015

A Directional Diffusion Algorithm for Inpainting.

Jan Deriu, Rolf Jagerman, Kai-En Tsay

CoRR, 2015

2014

The fifteen year struggle of decentralizing privacy-enhancing technology.

Rolf Jagerman, Wendo Sabée, Laurens Versluis, Martijn de Vos, Johan A. Pouwelse

CoRR, 2014