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of 442 551
pro vyhledávání: '"pate"'
Synthetic data created by differentially private (DP) generative models is increasingly used in real-world settings. In this context, PATE-GAN has emerged as a popular algorithm, combining Generative Adversarial Networks (GANs) with the private train
Externí odkaz:
http://arxiv.org/abs/2406.13985
Evaluating anomaly detection algorithms in time series data is critical as inaccuracies can lead to flawed decision-making in various domains where real-time analytics and data-driven strategies are essential. Traditional performance metrics assume i
Externí odkaz:
http://arxiv.org/abs/2405.12096
Conditional Generative Adversarial Networks (CGANs) exhibit significant potential in supervised learning model training by virtue of their ability to generate realistic labeled images. However, numerous studies have indicated the privacy leakage risk
Externí odkaz:
http://arxiv.org/abs/2404.12730