Lorenzo Rosasco: Learning Theory, Part 3 (variable selection (OMP), dimensionality reduction (PCA))

Topics: Determining which variables are important for prediction (e.g. given n patients and p genes, which genes are most important for prediction), sparsity (only some coefficients are non-zero), brute force, greedy approaches/matching pursuit, basis pursuit/lasso, unsupervised learning, dimensionality reduction, PCA