Adaptive Fair Representation Learning for Personalized Fairness in Recommendations via Information Alignment
Author:
Affiliation:
1. School of Computer Science, Sichuan University, Chengdu, China
Funder
National Natural Science Foundation of China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3626772.3657709
Reference42 articles.
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2. Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Li Wei, Yi Wu, Lukasz Heldt, Zhe Zhao, Lichan Hong, Ed H Chi, et al. 2019. Fairness in recommendation ranking through pairwise comparisons. In SIGKDD.
3. Asia J Biega Krishna P Gummadi and Gerhard Weikum. 2018. Equity of attention: Amortizing individual fairness in rankings. In SIGIR.
4. Avishek Bose and William Hamilton. 2019. Compositional fairness constraints for graph embeddings. In ICML.
5. Robin Burke Nasim Sonboli and Aldo Ordonez-Gauger. 2018. Balanced neighborhoods for multi-sided fairness in recommendation. In FAT$^*$ .
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