Covariance estimation is a fundamental statistical and machine learning problem concerning the inference of the covariance matrix of a random vector from limited observational data. This process is essential for characterizing the linear dependencies among variables and plays a critical role in numerous multivariate analyses, including principal component analysis, clustering, and financial risk management.