Fed-MPS: Federated learning with local differential privacy using model parameter selection for resource-constrained CPS
Summary
Fed-MPS: Federated learning with local differential privacy using model parameter selection for resource-constrained CPS is a scholarly article[1].
Key Facts
Fed-MPS: Federated learning with local differential privacy using model parameter selection for resource-constrained CPS's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). Fed-MPS: Federated learning with local differential privacy using model parameter selection for resource-constrained CPS. Retrieved May 24, 2026, from https://4ort.xyz/entity/fed-mps-federated-learning-with-local-differential-privacy-using-model-parameter-selection-for-resource-constrained-cps
MLA“Fed-MPS: Federated learning with local differential privacy using model parameter selection for resource-constrained CPS.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/fed-mps-federated-learning-with-local-differential-privacy-using-model-parameter-selection-for-resource-constrained-cps.
BibTeX@misc{4ortxyz_fed-mps-federated-learning-with-local-differential-privacy-using-model-parameter-selection-for-resource-constrained-cps_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Fed-MPS: Federated learning with local differential privacy using model parameter selection for resource-constrained CPS}}, year = {2026}, url = {https://4ort.xyz/entity/fed-mps-federated-learning-with-local-differential-privacy-using-model-parameter-selection-for-resource-constrained-cps}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Fed-MPS: Federated learning with local differential privacy using model parameter selection for resource-constrained CPS — https://4ort.xyz/entity/fed-mps-federated-learning-with-local-differential-privacy-using-model-parameter-selection-for-resource-constrained-cps (retrieved 2026-05-24)
