Unsupervised Learning and Nonlinear Dimension Reduction: Advances with Optimal Transport, Empirical Bayes, and Variational Inference
Description preview
Modern scientific data sets—ranging from single-cell RNA sequencing with tens of thousands of genes per patient, to galaxy-survey spectra with millions of stars, to user-item interaction matrices in online platforms—share two features: (i) ultra-high dimensionality and (ii) latent parameters that obey common structural laws (e.g., exchangeability,…
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