Explores the Decision Theory Framework in Statistical Theory, viewing statistics as a random game with key concepts like admissibility, minimax rules, and Bayes rules.
Covers topic models, focusing on Latent Dirichlet Allocation, clustering, GMMs, Dirichlet distribution, LDA learning, and applications in digital humanities.
Covers quantile regression, focusing on linear optimization for predicting outputs and discussing sensitivity to outliers, problem formulation, and practical implementation.
