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FedRAD: Heterogeneous Federated Learning via Relational Adaptive Distillation

Research article (Sensors, 2023) · cited 11× · AI/ML
academia openalex:W4384822670
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FedRAD: Heterogeneous Federated Learning via Relational Adaptive Distillation

Summary

FedRAD: Heterogeneous Federated Learning via Relational Adaptive Distillation is a scholarly article[1].

Key Facts

  • FedRAD: Heterogeneous Federated Learning via Relational Adaptive Distillation'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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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). FedRAD: Heterogeneous Federated Learning via Relational Adaptive Distillation. Retrieved May 24, 2026, from https://4ort.xyz/entity/fedrad-heterogeneous-federated-learning-via-relational-adaptive-distillation
MLA “FedRAD: Heterogeneous Federated Learning via Relational Adaptive Distillation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/fedrad-heterogeneous-federated-learning-via-relational-adaptive-distillation.
BibTeX @misc{4ortxyz_fedrad-heterogeneous-federated-learning-via-relational-adaptive-distillation_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{FedRAD: Heterogeneous Federated Learning via Relational Adaptive Distillation}}, year = {2026}, url = {https://4ort.xyz/entity/fedrad-heterogeneous-federated-learning-via-relational-adaptive-distillation}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): FedRAD: Heterogeneous Federated Learning via Relational Adaptive Distillation — https://4ort.xyz/entity/fedrad-heterogeneous-federated-learning-via-relational-adaptive-distillation (retrieved 2026-05-24)

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