Exposure Fairness

3 papers with code • 0 benchmarks • 0 datasets

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Most implemented papers

FairGAN: GANs-based Fairness-aware Learning for Recommendations with Implicit Feedback

jasonshere/FairGAN Proceedings of the ACM Web Conference 2022

To fill this gap, we propose a Generative Adversarial Networks (GANs) based learning algorithm FairGAN mapping the exposure fairness issue to the problem of negative preferences in implicit feedback data.

Joint Multisided Exposure Fairness for Recommendation

haolun-wu/jmefairness 29 Apr 2022

Prior research on exposure fairness in the context of recommender systems has focused mostly on disparities in the exposure of individual or groups of items to individual users of the system.

Scalable and Provably Fair Exposure Control for Large-Scale Recommender Systems

riktor/exadmm-recommender 22 Feb 2024

Typical recommendation and ranking methods aim to optimize the satisfaction of users, but they are often oblivious to their impact on the items (e. g., products, jobs, news, video) and their providers.