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- research-articleJuly 2023
Learning to Re-rank with Constrained Meta-Optimal Transport
SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information RetrievalJuly 2023, Pages 48–57https://doi.org/10.1145/3539618.3591714Many re-ranking strategies in search systems rely on stochastic ranking policies, encoded as Doubly-Stochastic (DS) matrices, that satisfy desired ranking constraints in expectation, e.g., Fairness of Exposure (FOE). These strategies are generally two-...
- introductionSeptember 2022
CONSEQUENCES — Causality, Counterfactuals and Sequential Decision-Making for Recommender Systems
RecSys '22: Proceedings of the 16th ACM Conference on Recommender SystemsSeptember 2022, Pages 654–657https://doi.org/10.1145/3523227.3547409Recommender systems are more and more often modelled as repeated decision making processes – deciding which (ranking of) items to recommend to a given user. Each decision to recommend or rank an item has a significant impact on immediate and future user ...
- research-articleJuly 2018
Fairness of Exposure in Rankings
KDD '18: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data MiningJuly 2018, Pages 2219–2228https://doi.org/10.1145/3219819.3220088Rankings are ubiquitous in the online world today. As we have transitioned from finding books in libraries to ranking products, jobs, job applicants, opinions and potential romantic partners, there is a substantial precedent that ranking systems have a ...