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Adversarial Examples Can Be Effective Data Augmentation for Unsupervised Machine Learning

Research article (Proceedings of the AAAI Conference on Artificial Intelligence, 2022) · cited 13× · AI/ML
academia openalex:W4206857759
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Adversarial Examples Can Be Effective Data Augmentation for Unsupervised Machine Learning

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Adversarial Examples Can Be Effective Data Augmentation for Unsupervised Machine Learning is a scholarly article[1].

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  • Adversarial Examples Can Be Effective Data Augmentation for Unsupervised Machine Learning's instance of is recorded as scholarly article[2].

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Adversarial Examples Can Be Effective Data Augmentation for Unsupervised Machine Learning. Retrieved May 24, 2026, from https://4ort.xyz/entity/adversarial-examples-can-be-effective-data-augmentation-for-unsupervised-machine-learning
MLA “Adversarial Examples Can Be Effective Data Augmentation for Unsupervised Machine Learning.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/adversarial-examples-can-be-effective-data-augmentation-for-unsupervised-machine-learning.
BibTeX @misc{4ortxyz_adversarial-examples-can-be-effective-data-augmentation-for-unsupervised-machine-learning_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Adversarial Examples Can Be Effective Data Augmentation for Unsupervised Machine Learning}}, year = {2026}, url = {https://4ort.xyz/entity/adversarial-examples-can-be-effective-data-augmentation-for-unsupervised-machine-learning}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Adversarial Examples Can Be Effective Data Augmentation for Unsupervised Machine Learning — https://4ort.xyz/entity/adversarial-examples-can-be-effective-data-augmentation-for-unsupervised-machine-learning (retrieved 2026-05-24)

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