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Differentially Private Distribution Release of Gaussian Mixture Models via KL-Divergence Minimization
Gaussian Mixture Models (GMMs) are widely used statistical models for representing multi-modal data distributions, with numerous applications in data mining, pattern recognition, data simulation, and machine learning. However, recent research has shown that releasing GMM parameters poses significant
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