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Failure-Resilient ML Inference at the Edge through Graceful Service Degradation

Research article (MILCOM 2023 - 2023 IEEE Military Communications Conference (MILCOM), 2023) · cited 10× · AI/ML
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Failure-Resilient ML Inference at the Edge through Graceful Service Degradation

Summary

Failure-Resilient ML Inference at the Edge through Graceful Service Degradation is a scholarly article[1].

Key Facts

  • Failure-Resilient ML Inference at the Edge through Graceful Service Degradation's instance of is recorded as scholarly article[2].

Related Entities

Prashant Shenoy Tarek Abdelzaher

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). Failure-Resilient ML Inference at the Edge through Graceful Service Degradation. Retrieved May 24, 2026, from https://4ort.xyz/entity/failure-resilient-ml-inference-at-the-edge-through-graceful-service-degradation
MLA “Failure-Resilient ML Inference at the Edge through Graceful Service Degradation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/failure-resilient-ml-inference-at-the-edge-through-graceful-service-degradation.
BibTeX @misc{4ortxyz_failure-resilient-ml-inference-at-the-edge-through-graceful-service-degradation_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Failure-Resilient ML Inference at the Edge through Graceful Service Degradation}}, year = {2026}, url = {https://4ort.xyz/entity/failure-resilient-ml-inference-at-the-edge-through-graceful-service-degradation}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Failure-Resilient ML Inference at the Edge through Graceful Service Degradation — https://4ort.xyz/entity/failure-resilient-ml-inference-at-the-edge-through-graceful-service-degradation (retrieved 2026-05-24)

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