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Toward Robust Graph Semi-Supervised Learning Against Extreme Data Scarcity

Research article (IEEE Transactions on Neural Networks and Learning Systems, 2024) · cited 12× · AI/ML
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Toward Robust Graph Semi-Supervised Learning Against Extreme Data Scarcity

Summary

Toward Robust Graph Semi-Supervised Learning Against Extreme Data Scarcity is a scholarly article[1].

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  • Toward Robust Graph Semi-Supervised Learning Against Extreme Data Scarcity's instance of is recorded as scholarly article[2].

Related Entities

Huan Liu

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

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  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). Toward Robust Graph Semi-Supervised Learning Against Extreme Data Scarcity. Retrieved May 24, 2026, from https://4ort.xyz/entity/toward-robust-graph-semi-supervised-learning-against-extreme-data-scarcity
MLA “Toward Robust Graph Semi-Supervised Learning Against Extreme Data Scarcity.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/toward-robust-graph-semi-supervised-learning-against-extreme-data-scarcity.
BibTeX @misc{4ortxyz_toward-robust-graph-semi-supervised-learning-against-extreme-data-scarcity_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Toward Robust Graph Semi-Supervised Learning Against Extreme Data Scarcity}}, year = {2026}, url = {https://4ort.xyz/entity/toward-robust-graph-semi-supervised-learning-against-extreme-data-scarcity}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Toward Robust Graph Semi-Supervised Learning Against Extreme Data Scarcity — https://4ort.xyz/entity/toward-robust-graph-semi-supervised-learning-against-extreme-data-scarcity (retrieved 2026-05-24)

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