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Relational Data Synthesis using Generative Adversarial Networks: A Design Space Exploration

Summary: Comprehensive experimental study of relational data synthesis with GANs in a unified framework, detailing a design space over architectures and training methods. Shows GANs' promise over traditional synthesis and offers design guidance plus future directions. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12092
Venue
VLDB
Year
2020
Pagerank
5.8540287e-05
Overall Rank
4,884 | 66.03%
DOI
10.14778/3407790.3407802

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