Meta-learning approach for variational autoencoder hyperparameter tuning
Synthetic data generation is a promising alternative to traditional data anonymization, with Variational Autoencoders (VAEs) excelling at generating high-quality synthetic tabular datasets. However, VAE hyperparameter selection is often computationally expensive or suboptimal. We propose a meta-lear...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Graz University of Technology
2025-06-01
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| Series: | Journal of Universal Computer Science |
| Subjects: | |
| Online Access: | https://lib.jucs.org/article/124087/download/pdf/ |
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