Bayesian Learning of Latent Variable Models

    59 2.4 Extensions of probabilistic PCA PCA of large-scale datasets with many missing values Principal component analysis (PCA) is a classical data analysis technique. Some algorithms for PCA scale better than others to problems with high dimensionality. They also differ in the ability to handle missing values in the data. In our recent papers [16, 17], a… CONTINUE READING