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Hardware-friendly User-specific Machine Learning for Edge Devices

Research article (ACM Transactions on Embedded Computing Systems, 2022) · cited 11× · AI/ML
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Hardware-friendly User-specific Machine Learning for Edge Devices

Summary

Hardware-friendly User-specific Machine Learning for Edge Devices is a scholarly article[1].

Key Facts

  • Hardware-friendly User-specific Machine Learning for Edge Devices's instance of is recorded as scholarly article[2].

Related Entities

Valeria Bertacco

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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). Hardware-friendly User-specific Machine Learning for Edge Devices. Retrieved May 24, 2026, from https://4ort.xyz/entity/hardware-friendly-user-specific-machine-learning-for-edge-devices
MLA “Hardware-friendly User-specific Machine Learning for Edge Devices.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/hardware-friendly-user-specific-machine-learning-for-edge-devices.
BibTeX @misc{4ortxyz_hardware-friendly-user-specific-machine-learning-for-edge-devices_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Hardware-friendly User-specific Machine Learning for Edge Devices}}, year = {2026}, url = {https://4ort.xyz/entity/hardware-friendly-user-specific-machine-learning-for-edge-devices}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Hardware-friendly User-specific Machine Learning for Edge Devices — https://4ort.xyz/entity/hardware-friendly-user-specific-machine-learning-for-edge-devices (retrieved 2026-05-24)

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