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FAIR: Quality-Aware Federated Learning with Precise User Incentive and Model Aggregation

Research article (IEEE INFOCOM 2021 - IEEE Conference on Computer Communications, 2021) · cited 197× · AI/ML
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FAIR: Quality-Aware Federated Learning with Precise User Incentive and Model Aggregation

Summary

FAIR: Quality-Aware Federated Learning with Precise User Incentive and Model Aggregation is a scholarly article[1].

Key Facts

  • FAIR: Quality-Aware Federated Learning with Precise User Incentive and Model Aggregation's instance of is recorded as scholarly article[2].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). FAIR: Quality-Aware Federated Learning with Precise User Incentive and Model Aggregation. Retrieved May 24, 2026, from https://4ort.xyz/entity/fair-quality-aware-federated-learning-with-precise-user-incentive-and-model-aggregation
MLA “FAIR: Quality-Aware Federated Learning with Precise User Incentive and Model Aggregation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/fair-quality-aware-federated-learning-with-precise-user-incentive-and-model-aggregation.
BibTeX @misc{4ortxyz_fair-quality-aware-federated-learning-with-precise-user-incentive-and-model-aggregation_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{FAIR: Quality-Aware Federated Learning with Precise User Incentive and Model Aggregation}}, year = {2026}, url = {https://4ort.xyz/entity/fair-quality-aware-federated-learning-with-precise-user-incentive-and-model-aggregation}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): FAIR: Quality-Aware Federated Learning with Precise User Incentive and Model Aggregation — https://4ort.xyz/entity/fair-quality-aware-federated-learning-with-precise-user-incentive-and-model-aggregation (retrieved 2026-05-24)

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