Artificial intelligence & Information retrieval

Author: mdr (Page 1 of 17)

New publications

Catching up again with recent and upcoming publications:

  • Qiannan Cheng, Zhaochun Ren, Yujie Lin, Pengjie Ren, Zhumin Chen, Xiangyuan Liu, and Maarten de Rijke. Long Short-Term Session Search with Joint Document Reranking and Next Query Prediction. In The Web Conference 2021. ACM, April 2021. Bibtex, PDF
    @inproceedings{cheng-2021-long,
    author = {Cheng, Qiannan and Ren, Zhaochun and Lin, Yujie and Ren, Pengjie and Chen, Zhumin and Liu, Xiangyuan and de Rijke, Maarten},
    booktitle = {The Web Conference 2021},
    date-added = {2021-01-15 20:42:20 +0100},
    date-modified = {2021-03-13 22:16:36 +0100},
    month = {April},
    publisher = {ACM},
    title = {Long Short-Term Session Search with Joint Document Reranking and Next Query Prediction},
    year = {2021}}
  • Ana Lucic, Madhulika Srikumar, Umang Bhatt, Alice Xiang, Ankur Taly, Vera Q. Liao, and Maarten de Rijke. A Multistakeholder Approach Towards Evaluating AI Transparency Mechanisms. arXiv preprint arXiv:2103.14976, March 2021. Bibtex, PDF, URL
    @article{lucic-2021-multistakeholder-arxiv,
    author = {Lucic, Ana and Srikumar, Madhulika and Bhatt, Umang and Xiang, Alice and Taly, Ankur and Liao, Q. Vera and de Rijke, Maarten},
    date-added = {2021-04-04 09:45:06 +0200},
    date-modified = {2021-04-04 09:48:22 +0200},
    journal = {arXiv preprint arXiv:2103.14976},
    month = {March},
    title = {A Multistakeholder Approach Towards Evaluating AI Transparency Mechanisms},
    url = {https://arxiv.org/pdf/2103.14976},
    year = {2021},
    Bdsk-Url-1 = {https://arxiv.org/pdf/2103.14976}}
  • Harrie Oosterhuis and Maarten de Rijke. Robust Generalization and Safe Query-Specialization in Counterfactual Learning to Rank. In The Web Conference 2021. ACM, April 2021. Bibtex, PDF
    @inproceedings{oosterhuis-2021-robust,
    author = {Oosterhuis, Harrie and de Rijke, Maarten},
    booktitle = {The Web Conference 2021},
    date-added = {2021-01-15 20:44:01 +0100},
    date-modified = {2021-01-15 20:44:33 +0100},
    month = {April},
    publisher = {ACM},
    title = {Robust Generalization and Safe Query-Specialization in Counterfactual Learning to Rank},
    year = {2021}}
  • Jiahuan Pei, Pengjie Ren, and Maarten de Rijke. A Cooperative Memory Network for Personalized Task-oriented Dialogue Systems with Incomplete User Profiles. In The Web Conference 2021. ACM, April 2021. Bibtex, PDF
    @inproceedings{pei-2021-cooperative,
    author = {Pei, Jiahuan and Ren, Pengjie and de Rijke, Maarten},
    booktitle = {The Web Conference 2021},
    date-added = {2021-01-15 20:40:35 +0100},
    date-modified = {2021-01-15 20:42:07 +0100},
    month = {April},
    publisher = {ACM},
    title = {A Cooperative Memory Network for Personalized Task-oriented Dialogue Systems with Incomplete User Profiles},
    year = {2021}}

New publications

Catching up with some new publications that appeared recently or are about to appear:

  • Chongming Gao, Wenqiang Lei, Xiangnan He, Maarten de Rijke, and Tat-Seng Chua. Advances and Challenges in Conversational Recommender Systems: A Survey. arXiv preprint arXiv:2101.09459, January 2021. Bibtex, PDF, URL
    @article{gao-2021-advances-arxiv,
    author = {Gao, Chongming and Lei, Wenqiang and He, Xiangnan and de Rijke, Maarten and Chua, Tat-Seng},
    date-added = {2021-02-21 16:37:14 +0100},
    date-modified = {2021-02-21 16:46:39 +0100},
    journal = {arXiv preprint arXiv:2101.09459},
    month = {January},
    title = {Advances and Challenges in Conversational Recommender Systems: A Survey},
    url = {https://arxiv.org/abs/2101.09459},
    year = {2021},
    Bdsk-Url-1 = {https://arxiv.org/abs/2101.09459}}
  • Qintong Li, Piji Li, Xinyi Li, Zhumin Chen, Zhaochun Ren, and Maarten de Rijke. Abstractive Opinion Tagging. In WSDM 2021: 14th International Conference on Web Search and Data Mining. ACM, March 2021. Bibtex, PDF
    @inproceedings{li-2021-abstractive,
    author = {Li, Qintong and Li, Piji and Li, Xinyi and Chen, Zhumin and Ren, Zhaochun and de Rijke, Maarten},
    booktitle = {WSDM 2021: 14th International Conference on Web Search and Data Mining},
    date-added = {2020-10-16 06:27:36 +0200},
    date-modified = {2020-10-16 06:27:36 +0200},
    month = {March},
    publisher = {ACM},
    title = {Abstractive Opinion Tagging},
    year = {2021}}
  • Ana Lucic, Maartje ter Hoeve, Gabriele Tolomei, Maarten de Rijke, and Fabrizio Silvestri. CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks. arXiv preprint arXiv:2102.03322, February 2021. Bibtex, PDF, URL
    @article{lucic-2021-cf-gnnexplainer-arxiv,
    author = {Lucic, Ana and ter Hoeve, Maartje and Tolomei, Gabriele and de Rijke, Maarten and Silvestri, Fabrizio},
    date-added = {2021-02-08 07:18:31 +0100},
    date-modified = {2021-02-08 07:25:21 +0100},
    journal = {arXiv preprint arXiv:2102.03322},
    month = {February},
    title = {CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks},
    url = {https://arxiv.org/pdf/2102.03322},
    year = {2021},
    Bdsk-Url-1 = {https://arxiv.org/pdf/2102.03322}}
  • Harrie Oosterhuis and Maarten de Rijke. Unifying Online and Counterfactual Learning to Rank. In WSDM 2021: 14th International Conference on Web Search and Data Mining. ACM, March 2021. Bibtex, PDF
    @inproceedings{oosterhuis-2021-unifying,
    author = {Oosterhuis, Harrie and de Rijke, Maarten},
    booktitle = {WSDM 2021: 14th International Conference on Web Search and Data Mining},
    date-added = {2020-10-16 06:27:40 +0200},
    date-modified = {2020-10-16 06:28:29 +0200},
    month = {March},
    publisher = {ACM},
    title = {Unifying Online and Counterfactual Learning to Rank},
    year = {2021}}

Come and Join Us at the IRLab

Come and work with us at the IRLab at the University of Amsterdam. Vacancies for fully funded PhD students, a research engineer, and an assistant professor.

We will shortly open a vacancy for an assistant professor at the intersection of machine learning and information retrieval. Come and build your own team. Stay tuned.

We will also open a position for a research engineer to support our team. Come and help us develop and share open source solutions and datasets, and keep our clusters spinning happily.

Open already: three vacancies for fully funded PhD students. Come and help us develop the next generation of conversational search. Deadline: November 30. See https://t.co/qTXIlFAmaE?amp=1

If you have any questions, please reach out to Evangelos Kanoulas, Ilya Markov, Sebastian Schelter, or me.

New publications

New publications that are scheduled to appear this month:

  • Wanyu Chen, Fei Cai, Honghui Chen, and Maarten de Rijke. Hierarchical Neural Query Suggestion with an Attention Mechanism. Information Processing & Management, 57(6):Article 102040, November 2020. Bibtex, PDF
    @article{chen-2020-hierarchical,
    author = {Chen, Wanyu and Cai, Fei and Chen, Honghui and de Rijke, Maarten},
    date-added = {2018-10-07 12:36:41 +0200},
    date-modified = {2020-10-21 06:23:07 +0200},
    journal = {Information Processing \& Management},
    month = {November},
    number = {6},
    pages = {Article 102040},
    title = {Hierarchical Neural Query Suggestion with an Attention Mechanism},
    volume = {57},
    year = {2020}}
  • Ziming Li, Sungjin Lee, Baolin Peng, Jinchao Li, Julia Kiseleva, Maarten de Rijke, Shahin Shayandeh, and Jianfeng Gao. Guided Dialogue Policy Learning without Adversarial Learning in the Loop. In EMNLP 2020. ACL, November 2020. Bibtex, PDF
    @inproceedings{li-2020-guided,
    author = {Li, Ziming and Lee, Sungjin and Peng, Baolin and Li, Jinchao and Kiseleva, Julia and de Rijke, Maarten and Shayandeh, Shahin and Gao, Jianfeng},
    booktitle = {EMNLP 2020},
    date-added = {2020-09-15 18:12:31 +0200},
    date-modified = {2020-09-15 18:18:32 +0200},
    month = {November},
    publisher = {ACL},
    title = {Guided Dialogue Policy Learning without Adversarial Learning in the Loop},
    year = {2020}}
  • Ziming Li, Julia Kiseleva, and Maarten de Rijke. Rethinking Supervised Learning and Reinforcement Learning in Task-Oriented Dialogue Systems. In EMNLP 2020. ACL, November 2020. Bibtex, PDF
    @inproceedings{li-2020-rethinking,
    author = {Li, Ziming and Kiseleva, Julia and de Rijke, Maarten},
    booktitle = {EMNLP 2020},
    date-added = {2020-09-15 18:18:49 +0200},
    date-modified = {2020-09-15 18:20:20 +0200},
    month = {November},
    publisher = {ACL},
    title = {Rethinking Supervised Learning and Reinforcement Learning in Task-Oriented Dialogue Systems},
    year = {2020}}
  • Jianming Zheng, Fei Cai, Honghui Chen, and Maarten de Rijke. Pre-train, Interact, Fine-tune: A Novel Interaction Representation for Text Classification. Information Processing & Management, 57(6):Article 102215, November 2020. Bibtex, PDF
    @article{zheng-2020-pre-train,
    author = {Zheng, Jianming and Cai, Fei and Chen, Honghui and de Rijke, Maarten},
    date-added = {2020-01-26 21:09:35 +0100},
    date-modified = {2020-10-21 06:24:01 +0200},
    journal = {Information Processing \& Management},
    month = {November},
    number = {6},
    pages = {Article 102215},
    title = {Pre-train, Interact, Fine-tune: A Novel Interaction Representation for Text Classification},
    volume = {57},
    year = {2020}}

New publications

New publications that are scheduled to appear this month:

  • Wanyu Chen, Pengjie Ren, Fei Cai, Fei Sun, and Maarten de Rijke. Improving End-to-End Sequential Recommendations with Intent-aware Diversification. In CIKM 2020: 29th ACM International Conference on Information and Knowledge Management, page 175–184. ACM, October 2020. Bibtex, PDF
    @inproceedings{chen-2020-improving,
    author = {Chen, Wanyu and Ren, Pengjie and Cai, Fei and Sun, Fei and de Rijke, Maarten},
    booktitle = {CIKM 2020: 29th ACM International Conference on Information and Knowledge Management},
    date-added = {2020-07-17 12:46:55 +0200},
    date-modified = {2020-10-20 07:31:14 +0200},
    month = {October},
    pages = {175--184},
    publisher = {ACM},
    title = {Improving End-to-End Sequential Recommendations with Intent-aware Diversification},
    year = {2020}}
  • Xiangsheng Li, Maarten de Rijke, Yiqun Liu, Jiaxin Mao, Weizhi Ma, Min Zhang, and Shaoping Ma. Learning Better Representations for Neural Information Retrieval with Graph Information. In CIKM 2020: 29th ACM International Conference on Information and Knowledge Management, page 795–804. ACM, October 2020. Bibtex, PDF
    @inproceedings{li-2020-learning,
    author = {Li, Xiangsheng and de Rijke, Maarten and Liu, Yiqun and Mao, Jiaxin and Ma, Weizhi and Zhang, Min and Ma, Shaoping},
    booktitle = {CIKM 2020: 29th ACM International Conference on Information and Knowledge Management},
    date-added = {2020-07-17 12:41:46 +0200},
    date-modified = {2020-10-20 07:31:34 +0200},
    month = {October},
    pages = {795--804},
    publisher = {ACM},
    title = {Learning Better Representations for Neural Information Retrieval with Graph Information},
    year = {2020}}
  • Zhiqiang Pan, Fei Cai, Wanyu Chen, Honghui Chen, and Maarten de Rijke. Star Graph Neural Networks for Session-based Recommendation. In CIKM 2020: 29th ACM International Conference on Information and Knowledge Management, page 1195–1204. ACM, October 2020. Bibtex, PDF
    @inproceedings{pan-2020-star,
    author = {Pan, Zhiqiang and Cai, Fei and Chen, Wanyu and Chen, Honghui and de Rijke, Maarten},
    booktitle = {CIKM 2020: 29th ACM International Conference on Information and Knowledge Management},
    date-added = {2020-07-17 12:44:13 +0200},
    date-modified = {2020-10-20 07:31:54 +0200},
    month = {October},
    pages = {1195--1204},
    publisher = {ACM},
    title = {Star Graph Neural Networks for Session-based Recommendation},
    year = {2020}}
  • Ridho Reinanda, Edgar Meij, and Maarten de Rijke. Knowledge Graphs: An Information Retrieval Perspective. Foundations and Trends in Information Retrieval, 14(4):289–444, October 2020. Bibtex, PDF
    @article{reinanda-2020-knowledge,
    author = {Reinanda, Ridho and Meij, Edgar and de Rijke, Maarten},
    date-added = {2018-07-20 09:10:39 +0000},
    date-modified = {2020-10-16 22:32:43 +0200},
    journal = {Foundations and Trends in Information Retrieval},
    month = {October},
    number = {4},
    pages = {289--444},
    title = {Knowledge Graphs: An Information Retrieval Perspective},
    volume = {14},
    year = {2020}}
  • Ali Vardasbi, Harrie Oosterhuis, and Maarten de Rijke. When Inverse Propensity Scoring does not Work: Affine Corrections for Unbiased Learning to Rank. In CIKM 2020: 29th ACM International Conference on Information and Knowledge Management, page 1475–1484. ACM, October 2020. Bibtex, PDF
    @inproceedings{vardasbi-2020-inverse,
    author = {Vardasbi, Ali and Oosterhuis, Harrie and de Rijke, Maarten},
    booktitle = {CIKM 2020: 29th ACM International Conference on Information and Knowledge Management},
    date-added = {2020-07-17 12:38:45 +0200},
    date-modified = {2020-10-20 07:32:14 +0200},
    month = {October},
    pages = {1475--1484},
    publisher = {ACM},
    title = {When Inverse Propensity Scoring does not Work: Affine Corrections for Unbiased Learning to Rank},
    year = {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.

Fully funded PhD position on task-based question answering

Interested in developing conversational systems that support scientific discovery? In question answering algorithms that are able to gather and synthesize complex answers in the task-based setting of a research platform? We have a fully funded PhD position in which you can develop neural models that can retrieve or generate answers from structured and unstructured resources conditioned on inferred or detected task and intent, as part of the Discovery Lab. For details, please visit https://www.uva.nl/en/content/vacancies/2020/08/20-470-phd-position-on-task-based-question-answering.html. The deadline is September 15, 2020.

New publications

Some new papers that are scheduled to appear this month:

  • Zeynep Akata, Dan Balliet, Maarten de Rijke, Frank Dignum, Virginia Dignum, Guszti Eiben, Antske Fokkens, Davide Grossi, Koen Hindriks, Holger Hoos, Haley Hung, Catholijn Jonker, Christof Monz, Mark Neerincx, Frans Oliehoek, Henri Prakken, Stefan Schlobach, Linda van der Gaag, Frank van Harmelen, Herke van Hoof, Birna van Riemsdijk, Aimee van Wynsberghe, Rineke Verbrugge, Bart Verheij, Piek Vossen, and Max Welling. A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence. Computer, 53(08):18-28, August 2020. Bibtex, PDF
    @article{akata-2020-research,
    author = {Akata, Zeynep and Balliet, Dan and de Rijke, Maarten and Dignum, Frank and Dignum, Virginia and Eiben, Guszti and Fokkens, Antske and Grossi, Davide and Hindriks, Koen and Hoos, Holger and Hung, Haley and Jonker, Catholijn and Monz, Christof and Neerincx, Mark and Oliehoek, Frans and Prakken, Henri and Schlobach, Stefan and van der Gaag, Linda and van Harmelen, Frank and van Hoof, Herke and van Riemsdijk, Birna and van Wynsberghe, Aimee and Verbrugge, Rineke and Verheij, Bart and Vossen, Piek and Welling, Max},
    date-added = {2020-08-11 21:26:55 +0200},
    date-modified = {2020-08-11 21:30:19 +0200},
    journal = {Computer},
    month = {August},
    number = {08},
    pages = {18-28},
    title = {A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence},
    volume = {53},
    year = {2020},
    Bdsk-Url-1 = {https://doi.org/10.1109/MC.2020.2996587}}
  • Yifan Chen, Yang Wang, Xiang Zhao, Jie Zou, and Maarten de Rijke. Block-aware Item Similarity Models for Top-$N$ Recommendation. ACM Transactions on Information Systems, 38(4):Article 42, September 2020. Bibtex, PDF
    @article{chen-2020-block-aware,
    author = {Chen, Yifan and Wang, Yang and Zhao, Xiang and Zou, Jie and de Rijke, Maarten},
    date-added = {2019-12-07 08:29:15 +0100},
    date-modified = {2020-09-11 07:41:45 +0200},
    journal = {ACM Transactions on Information Systems},
    month = {September},
    number = {4},
    pages = {Article 42},
    title = {Block-aware Item Similarity Models for Top-$N$ Recommendation},
    volume = {38},
    year = {2020}}
  • Chang Li, Ilya Markov, Maarten de Rijke, and Masrour Zoghi. MergeDTS: A Method for Effective Large-scale Online Ranker Evaluation. ACM Transactions on Information Systems, 38(4):Article 40, September 2020. Bibtex, PDF
    @article{li-2020-mergedts,
    author = {Li, Chang and Markov, Ilya and de Rijke, Maarten and Zoghi, Masrour},
    date-added = {2018-12-01 09:14:01 +0100},
    date-modified = {2020-09-11 07:42:03 +0200},
    journal = {ACM Transactions on Information Systems},
    month = {September},
    number = {4},
    pages = {Article 40},
    title = {MergeDTS: A Method for Effective Large-scale Online Ranker Evaluation},
    volume = {38},
    year = {2020}}
  • Yujie Lin, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Jun Ma, and Maarten de Rijke. Explainable Fashion Recommendation with Joint Outfit Matching and Comment Generation. IEEE Transactions on Knowledge and Data Engineering, 32(8):1502–1516, August 2020. Bibtex, PDF
    @article{lin-2020-explainable,
    author = {Lin, Yujie and Ren, Pengjie and Chen, Zhumin and Ren, Zhaochun and Ma, Jun and de Rijke, Maarten},
    date-added = {2018-06-19 19:07:42 +0000},
    date-modified = {2020-07-09 07:23:00 +0200},
    journal = {IEEE Transactions on Knowledge and Data Engineering},
    month = {August},
    number = {8},
    pages = {1502--1516},
    title = {Explainable Fashion Recommendation with Joint Outfit Matching and Comment Generation},
    volume = {32},
    year = {2020}}

Fully funded PhD position on explainable de-biasing in learning from interaction data

Modern search, recommendation and conversational systems learn from interactions with their users. Interested in developing new algorithms for learning from interaction data? In making this type of learning explainable? In removing bias from interaction data? And in making the de-biasing process as transparent as possible? We have a fully funded PhD position in which you can contribute to these questions as part of the Hybrid Intelligence project. For details, please visit https://www.uva.nl/en/content/vacancies/2020/07/20-458-phd-position-on-explainable-de-biasing-in-learning-from-interactions.html Deadline: August 31, 2020.

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