Artificial intelligence & Information retrieval

Month: September 2020

New publications

New publications that are scheduled to appear this month:

  • Mozhdeh Ariannezhad, Sebastian Schelter, and Maarten de Rijke. Demand Forecasting in the Presence of Privileged Information. In AALTD: International Workshop on Advanced Analytics and Learning on Temporal Data, LNCS 12588, pages 46-62. Springer, December 2020. Bibtex, PDF
    @inproceedings{ariannezhad-2020-demand,
    author = {Ariannezhad, Mozhdeh and Schelter, Sebastian and de Rijke, Maarten},
    booktitle = {AALTD: International Workshop on Advanced Analytics and Learning on Temporal Data},
    date-added = {2020-07-16 18:11:34 +0200},
    date-modified = {2020-12-29 23:04:14 +0100},
    month = {December},
    pages = {46-62},
    publisher = {Springer},
    series = {LNCS 12588},
    title = {Demand Forecasting in the Presence of Privileged Information},
    year = {2020}}
  • Jin Huang, Harrie Oosterhuis, Maarten de Rijke, and Herke van Hoof. Keeping Dataset Biases out of the Simulation: A Debiased Simulator for Reinforcement Learning based Recommender Systems. In RecSys 2020: The ACM Conference on Recommender Systems, page 190–199. ACM, September 2020. Bibtex, PDF
    @inproceedings{huang-2020-keeping,
    author = {Huang, Jin and Oosterhuis, Harrie and de Rijke, Maarten and van Hoof, Herke},
    booktitle = {RecSys 2020: The ACM Conference on Recommender Systems},
    date-added = {2020-07-23 08:03:19 +0200},
    date-modified = {2020-09-19 09:47:04 +0200},
    month = {September},
    pages = {190--199},
    publisher = {ACM},
    title = {Keeping Dataset Biases out of the Simulation: A Debiased Simulator for Reinforcement Learning based Recommender Systems},
    year = {2020}}
  • Chang Li, Haoyun Feng, and Maarten de Rijke. Cascading Hybrid Bandits: Online Learning to Rank for Relevance and Diversity. In RecSys 2020: The ACM Conference on Recommender Systems, page 33–42. ACM, September 2020. Bibtex, PDF
    @inproceedings{li-2020-cascading,
    author = {Li, Chang and Feng, Haoyun and de Rijke, Maarten},
    booktitle = {RecSys 2020: The ACM Conference on Recommender Systems},
    date-added = {2020-07-23 07:41:55 +0200},
    date-modified = {2020-09-19 09:46:34 +0200},
    month = {September},
    pages = {33--42},
    publisher = {ACM},
    title = {Cascading Hybrid Bandits: Online Learning to Rank for Relevance and Diversity},
    year = {2020}}
  • Harrie Oosterhuis and Maarten de Rijke. Taking the Counterfactual Online: Efficient and Unbiased Online Evaluation for Ranking. In ICTIR 2020: The 6th ACM International Conference on the Theory of Information Retrieval, page 137–144. ACM, September 2020. Bibtex, PDF
    @inproceedings{oosterhuis-2020-taking,
    author = {Oosterhuis, Harrie and de Rijke, Maarten},
    booktitle = {ICTIR 2020: The 6th ACM International Conference on the Theory of Information Retrieval},
    date-added = {2020-06-30 10:31:31 +0200},
    date-modified = {2020-09-15 06:54:46 +0200},
    month = {September},
    pages = {137--144},
    publisher = {ACM},
    title = {Taking the Counterfactual Online: Efficient and Unbiased Online Evaluation for Ranking},
    year = {2020}}
  • Chuan Wu, Evangelos Kanoulas, and Maarten de Rijke. It All Starts with Entities: A Salient Entity Topic Model. Natural Language Engineering, 26(5):531–549, September 2020. Bibtex, PDF
    @article{wu-2020-all,
    author = {Wu, Chuan and Kanoulas, Evangelos and de Rijke, Maarten},
    date-added = {2018-09-21 10:00:04 +0200},
    date-modified = {2020-08-12 06:43:39 +0200},
    journal = {Natural Language Engineering},
    month = {September},
    number = {5},
    pages = {531--549},
    title = {It All Starts with Entities: A Salient Entity Topic Model},
    volume = {26},
    year = {2020}}

A New Team

As one of the research teams at the Informatics Institute, ILPS, the Information and Language Processing Systems group, has been around since April 1, 2004. During the past 16+ years, I have been fortunate enough enough to welcome, and work with, a large number of extremely talented PhD students, postdocs and staff members at ILPS.

In recent years, ILPS has grown to a team of 50+ people, a size where we need to organize ourselves differently, to make sure that communicate remains effective and that the team continues to function as a team.

We are breaking up ILPS into two new teams. One team is the Information Retrieval Lab, IRLab, led by Evangelos Kanoulas. The other team is the Language Technology Lab, led by Christof Monz. I will be part of the IRLab, together with my PhD students and postdocs.

© 2021 Maarten de Rijke

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