Social Choice for Heterogeneous Fairness in Recommendation
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- Social Choice for Heterogeneous Fairness in Recommendation
Recommendations
Dynamic Fairness-aware Recommendation Through Multi-agent Social Choice
Algorithmic fairness in the context of personalized recommendation presents significantly different challenges to those commonly encountered in classification tasks. Researchers studying classification have generally considered fairness to be a matter of ...
Multi-agent Social Choice for Dynamic Fairness-aware Recommendation
UMAP '22 Adjunct: Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and PersonalizationThe pursuit of algorithmic fairness requires that we think differently about the idea of the “user” in personalized systems, such as recommender systems. The conventional definition of the user in such systems focuses on the receiver of recommendations,...
Airtime Fairness for IEEE 802.11 Multirate Networks
Under a multi rate network scenario, the IEEE 802.11 DCF MAC fails to provide air-time fairness for all competing stations since the protocol is designed for ensuring max-min throughput fairness and the maximum achievable throughput by any station gets ...
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- SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
- SIGAI: ACM Special Interest Group on Artificial Intelligence
- SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
- SIGIR: ACM Special Interest Group on Information Retrieval
- SIGCHI: ACM Special Interest Group on Computer-Human Interaction
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Association for Computing Machinery
New York, NY, United States
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- Refereed limited
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- National Science Foundation
- Fulbright Commission
- Slovak Research and Development Agency
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