Overview
Syllabus
Intro
dimensionality as an enemy
collaborators who do real problems
reducing dimensionality
making reasonable assumptions
notation
mutual information
graphical models
characterizations
models
information theory
Blessings of dimensionality
Empirical results
Latent remodeling
Normal approach
Global optimization
Conditional independence
generative model link perspective
Independence of disease
Unconstrained optimization
Cluster structure recovery
Covariance estimation
Neuroscience
Data set
Brain pictures
Factor analysis
Cluster recovery
Improving reproducibility
unsupervised dimensionality reduction
Cohens D
PCA
ICA
Taught by
Santa Fe Institute