The paper presents a new approach, PrivPGD, for differentially private data synthesis of protected tabular datasets, an important task in sensitive domains like healthcare and government. Existing methods typically use…
Continue readingThe paper presents a novel method called Optimal Transport-guided Conditional Score-based Diffusion Model (OTCS) to deal with real-world applications that have unpaired or partially paired data. The method establishes a…
Continue readingThis article presents OTMatch, a new method for semi-supervised learning that leverages the semantic relationships among classes using an optimal transport loss function. The paper highlights that current algorithms often…
Continue readingThis paper proposes a novel deep learning-based framework for solving variational problems, with a focus on optimal transport. The dynamical formulation of optimal transport can be extended through different choices…
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