High-accuracy low-cost privacy-preserving federated learning in IoT systems via adaptive perturbation
Summary
High-accuracy low-cost privacy-preserving federated learning in IoT systems via adaptive perturbation is a scholarly article[1].
Key Facts
High-accuracy low-cost privacy-preserving federated learning in IoT systems via adaptive perturbation's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). High-accuracy low-cost privacy-preserving federated learning in IoT systems via adaptive perturbation. Retrieved May 24, 2026, from https://4ort.xyz/entity/high-accuracy-low-cost-privacy-preserving-federated-learning-in-iot-systems-via-adaptive-perturbation
MLA“High-accuracy low-cost privacy-preserving federated learning in IoT systems via adaptive perturbation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/high-accuracy-low-cost-privacy-preserving-federated-learning-in-iot-systems-via-adaptive-perturbation.
BibTeX@misc{4ortxyz_high-accuracy-low-cost-privacy-preserving-federated-learning-in-iot-systems-via-adaptive-perturbation_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{High-accuracy low-cost privacy-preserving federated learning in IoT systems via adaptive perturbation}}, year = {2026}, url = {https://4ort.xyz/entity/high-accuracy-low-cost-privacy-preserving-federated-learning-in-iot-systems-via-adaptive-perturbation}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): High-accuracy low-cost privacy-preserving federated learning in IoT systems via adaptive perturbation — https://4ort.xyz/entity/high-accuracy-low-cost-privacy-preserving-federated-learning-in-iot-systems-via-adaptive-perturbation (retrieved 2026-05-24)
