Real-world embodiments of recommender systems are increasingly often posed as decision-making systems, imposing consequences on the world around them. The literature on causal and counterfactual inference allows us to reason about these consequences, and better understand their implications. Whilst this research area h...
Olivier Jeunen, Harrie Oosterhuis, Flavian Vasile et al.· Proceedings of the 20th ACM...· 0 citations
Findings demonstrate that focusing only on single-attribute mitigation techniques is insufficient to ensure equitable outcomes across all population groups, and that intersectional evaluation is essential for developing fair and socially responsible educational prediction systems.
E. Lazar, Harrie Oosterhuis, Luca Consoli· 0 citations
This work considerably improves RL for LTR methodology by increasing its effectiveness, efficiency, and ease of application, and proposes an abstraction that places gradient estimation behind a document-exposure distribution that enables seamless plug-and-play integration with auto-differentiation.
Harrie Oosterhuis, R. Jagerman, Zhen Qin et al.· International Conference on...· 0 citations
This work demonstrates that PFNs, which are originally trained for classification, successfully outperform classification baselines on ranking data and introduces a novel sampling and inference scheme to obtain pairwise predictions from PFNs' native pointwise architecture, analogous to pairwise LTR.
David Vos, Samarth Bhargav, M. D. Rijke et al.· International Conference on...· 0 citations
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