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Critical Challenges and Guidelines in Evaluating Synthetic Tabular Data: A Systematic Review

Fuente: arXiv

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Dettagli Bibliografici
Autori principali:	Nafis, Nazia, Esnaola, Inaki, Martinez-Perez, Alvaro, Villa-Uriol, Maria-Cruz, Osmani, Venet
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Artificial Intelligence Computers and Society
Accesso online:	Acceder al recurso
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